BE1020636A3 - A METHOD FOR DIVIDELY DELAYED STREAMING OF CONTENT. - Google Patents

Description

A method for distributed delayed content streaming

The announcement relates to human behavior, and, more specifically, to a user interface that is optimized for brain task delimitation to mimic experience and buying behavior. The present invention relates to a system for accurately modeling a buyer / purchaser's psychology and arranging content objects in a user-initiated browsing and presentation channel, consisting of a neuropsychological modeling engine, an ranking application, and a behavioral model color that communicate with each other and a presentation system for communication networks. The neuropsychological modeling engine uses metafiles associated with content objects, a buyer / viewer model, and a channel model to derive a value die representing an individual's state of mind and a value m representing an individual's motivational strength to select a content object. If the value Ψ is within an acceptable predetermined range, the value m is used to prepare an arrangement for the content object in relation to other content objects associated with the channel model. Also disclosed are a system and technique for simultaneously presenting multiple data streams with content objects on the user interface in a manner that encourages multidimensional browsing, using traditional navigation controls.

Background

According to neurophysiology and neuropsychology, a human brain comprises a left hemisphere and a right hemisphere, each with its own personality or consciousness and a separate way of processing information. For simplicity, these will be referred to as the left half and the right half respectively. The left half of the brain is known for analytical, categorical thinking and textual, sequential processing. The right half of the brain is known for plastic, intuitive, holistic thinking and visual-spatial, parallel processing. Therefore, some processes or even simple exposure to certain stimuli will instead activate the right hemisphere and some other place of the left hemisphere.

For example, textual information will activate the left hemisphere and visual-spatial information will activate the right hemisphere. Similarly, the act of searching through the menus will rather activate the left hemisphere, while navigating with eg.

a joystick through a landscape or space rather than the right half will activate. Therefore, experiencing interfaces will rather activate the left or right half, depending on the type of elements used for the interfaces: eg visual-spatial elements or the text. Such left-right activation will also depend on the type of actions and thinking that are needed to use these elements.

As explained in the rest of this text, hemispheric brain activity can also be linked to human emotions and moods. For example, a product interface can support a certain mood, depending on how the front-end and back-end are designed, and depending on the processes needed to operate such interface.

The problem with current human interfaces is that they oblige us to process information or perform actions that are not in line with the voting experience for which the product was designed. Or, in other words, at some point during the user experience, these interfaces tend to activate a part of the brain, which then changes our emotions and therefore our mood in a non-desirable way. For example, people watch television to relax. Going through menus is an unwelcome break when one is in a relaxed atmosphere: it changes our mood from relaxation to frustration.

There is a need for a technique that assumes the desired experienced mood and derives the experience interface including its front-end design, back-end design and its operation, taking into account the mood swings caused by the specific brain activity required for the interface of process and work flow.

There is also a need for an interface that puts people in the right mood for certain activities or processes that are not yet optimally served today. Such applications, underserved from the experience point of view, are illustrated and grouped in six designs.

There is a need for a system and technique that makes products or content, for example audio, video, graphic, advertising, website, brochure, etc. are pre-selected from one or more content sources and are presented with a higher degree of accuracy, in particular an individual taste or the desired mood on a certain platform and to ask for a specific type of transaction.

There is a need for an e-reader black and white text representation emulator with which the user can display the figures in color or 3D by performing a simple, intuitive operation that keeps the user relaxed and does not require him to go through menus , or text or keywords or even changing platforms

There is a need for a web-based system that allows more automated recurring purchases. Such a system is not only a more efficient and relaxed alternative to state-of-the-art web shopping, but also to traditional supermarket shopping.

There is a need for an automatic securities trading system that takes into account buyers and sellers' moods and performs automated trading activities accordingly. There is a need for a trading system that supports the left hemisphere's task of risk management and at the same time blocks the right hemisphere's pursuit of profit.

There is a need for a model that links a buyer's typical emotions and mood, related to a specific type of sale, to an appropriate sales strategy.

SUMMARY OF THE INVENTION

The disclosure relates to a neuropsychological modeling technique and the resulting mathematical model for human emotions and moods applied in buyer, seller, user and psychology experience, more specifically applied in experience, interface, platform, process, and back end design of products, processes or services. Natural experiences interfaces are based on specific characteristics of the left and right consciousness, applied in the left hemisphere, right hemisphere or tandem interfaces.

Based on the modeling technique or model, a natural user experience mood is chosen, which dictates the design of the user interface and the back-end of the product, process or service in question.

The model or modeling technique therefore forms the basis of the design of the natural user experience, the user interface, the product process or workflow as well as the back-end.

Such neuropsychological model technique or model or the natural user experience or its interface or its back-end process can be applied in various designs, including but not limited to: 1) An internet and / or media and / or TV experience on it system, using a specific right brain interface and a tandem interface on different hardware platforms 2) A tandem interface for reading and / or research and / or writing, 3) A tandem user interface for that allows automatic buying on the internet for repeat consumer purchases.

4) An automatic system for trading securities, 5) An automatic internet bank or investment fund and 6) a model for sales training, consultancy and software.

Therefore, and more generally, there is a need for a neuropsychological modeling technique and model that links basic human emotions, moods, and cortical activity, interface design strategies including their back-end, front-end, and operational process of human experiences. Experiences are understood as moods that occur naturally and optimally in certain processes. Interfaces between these processes and the experiences in the human brain are optimally designed to support the natural and optimal experience at every stage of the process. So left, right and tandem interfaces are used, with specific cortical request to lure specific moods. In addition to the modeling technique and associated inventions, six other inventions are presented to support the specific, practical relevance and technical implementation as the embodiment of the modeling technique in specific applications.

The present invention relates to, but is not limited to: 1. A recommendation system functionally linked to a network-accessible source of the indexed content objects and a viewer system, the recommendation system capable of modeling the buyer / buyer psychology, the recommendation system comprising: a a neuropsychological modeling engine operably linked to the network-accessible source of indexed content objects; b. a behavioral modeler, functionally linked to the viewer system; c. a ranking application operatively linked to the neuropsychological modeling engine; d. a first memory, operably linked to the ranking application, the neuropsychological modeling engine, and the behavioral modeller for storing a plurality of viewer models; e. a second memory, operatively linked to the ranking application, the neuropsychological modeling engine, and the behavioral modeler for storing channel models and content object arrangements in relation to a channel model; wherein the neuropsychological modeling engine is configured to: i) compare meta-data associated with a content object, received from the source of indexed content objects, meta-data associated with a viewer model and at least one viewer channel associated with the viewer, and ii) determining whether the received content object is eligible to be arranged among other content objects associated with the viewer channel in accordance with the viewer's emotional motivation to select the content object.

2. The system according to point 1, wherein the recommendation system further comprises: f. a mathematical model for human emotions, stored in memory and accessible to the neuropsychological modeling engine.

The system of points 1 or 2 wherein the neuropsychological modeling engine is further configured to: iii) generate a fear vector value representing an individual's fear of selecting or purchasing the content object; iv) generate a desire vector value that represents an individual's desire to select or purchase the offered item; v) derive a value Ψ from the desire vector value and the fear vector value, which represents an individual's state of mind; vi) deriving a value m from the desire vector value and the fear vector value, which represents an individual's motivational strength to select the content object; and vii) if the value Ψ representing an individual's state of mind is within an acceptable predetermined range, provide the value m to the ranking application.

The system according to points 1 to 3, wherein the ranking application is configured to determine, using the value m received from the neuropsychological modeling engine, a ranking for the content object in relation to other content objects associated with the channel model.

5. A system consisting of a recommendation system according to one of points 1 to 4 and one or more content objects arranged and / or offered by the recommendation system.

A method for modeling the psychology of a buyer / buyer, comprising: a. Comparing meta-data associated with a content object with meta-data associated with a channel model; b. generating a fear vector value that represents an individual's fear of selecting or purchasing the content object; c. generating a desire vector value that represents an individual's desire to select or purchase the offered item; d. deriving, from the desire vector value and the fear vector value, a value Ψ representing an individual's state of mind; e. deriving, from the desire vector value and the fear vector value, a value m that represents an individual's motivational strength to select or purchase the content object; and f. if the value Ψ representing an individual's state of mind is within an acceptable predetermined range, using the value m to determine a ranking for the content object in relation to other content objects associated with the channel model; scary. storing the channel model and a viewing model associated with the individual in a network-accessible memory.

A system for modeling the psychology of a buying / buying buyer, consisting of: a. A first network-accessible memory for storing at least one channel model; b. a modeling engine, functionally coupled to the network-accessible memory and configured to compare meta-data associated with a content object with meta-data associated with the channel model and to generate: i) a fear vector value that an individual fears (repulsion) proposes to select or purchase the content object; ii) a desire vector value that represents an individual's desire to select or purchase the item offered; iii) a value Ψ representing an individual's state of mind, the value Ψ derived from the desire vector value and the fear vector value; iv) a value m representing an individual's motivational strength to select the content object, the value m derived from the desire vector value and the fear vector value; and c. an arrangement module responsive to the modeling engine to derive an arrangement for the content object in relation to other content objects associated with the channel model, from the value m generated by the modeling engine, if the value Ψ generated by the modeling engine is within an acceptable predetermined range ; and d. a second network-accessible memory for storing at least a portion of the content object and the other content objects.

8. A system consisting of a system according to point 7 and one or more content objects arranged by the system according to point 7.

A method for enabling multi-dimensional surfing, comprising: a. Evaluating a first content object corresponding to behavioral metadata associated with a consumer to determine eligibility for ranking; b. assigning an emotional motivation value to the first content object, if eligible for ranking; and c. arranging a reference to the first content object between a first plurality of references to content objects in order of increasing or decreasing emotional motivation associated with the respective content objects.

10. The method according to point 9, further comprising: d. assigning a chronological ranking value to the first content object between a second plurality of content objects with at least one parameter value in common with the first content object.

The method according to points 9 or 10, further comprising: e. arranging the first content object between a second plurality of content objects with at least one parameter value in common with the first content object in order of increasing or decreasing chronological ranking value.

A method for use with a video display system consisting of a video screen and a plurality of cursor navigation controls to sequentially move a user-selectable sub-area of the video screen surface in one or more directions, the method comprising: a. Receiving a first cursor navigation command; and B. forwarding the first cursor navigation command to start a presentation of a first content object from a first plurality of content objects that were previously arranged according to chronological order or progressively increasing or decreasing emotional motivation.

13. In a video display system consisting of: - a video screen; - a plurality of directional navigation controls to sequentially move a user selectable portion of the video screen in one or more directions over the video screen surface; - control logic for receiving command signals associated with one of the navigation controls and for passing the command signal to start a presentation of a first content object from a first plurality of content objects arranged in order of progressive emotional motivation; - wherein selection of a navigation control associated with a first direction starts a presentation of the first content object with at least the same or an increased emotional value than a previously presented content object; and - wherein the selection of a navigation control associated with a second direction, opposite the first direction, starts a presentation of the first content object with at least the same or reduced emotional motivation than a previously presented content object; and a plurality of memory buffers for storing at least a portion of the first plurality of content objects and the first content object.

14. The system according to item 13, further comprising: - control logic for receiving command signals associated with one of the navigation controls and for routing command signals to start a presentation of the first content object from a second plurality of content objects previously arranged in chronological order.

15. In a video display system, consisting of: - a video screen; - a plurality of directional navigation controls for sequentially moving a user selectable portion of the video screen in one or more directions over the video screen surface; - control logic for receiving command signals associated with one of the navigation controls and for selecting a first content object from a first plurality of content objects arranged in order of rising or falling emotional motivation and to start a presentation of the first content object from a second plurality to content objects previously arranged in chronological order.

16. In a video display system, comprising: a video screen; - a plurality of directional navigation controls for sequentially moving a user selectable portion of the video screen in one or more directions over the video screen surface; control logic for receiving command signals associated with one of the navigation controls and for passing the command signal to start a presentation of the first content object from a first plurality of content objects previously arranged in chronological order.

- wherein selecting a navigation control associated with a first direction starts a presentation of the first content object with a prior chronological value than a previously presented content object; and - wherein selecting a navigation control associated with a second direction, opposite to the first direction, starts a presentation of the first content object with a later chronological value than a previously presented content object; and - a plurality of memory buffers to store at least a portion of the first plurality of content objects and the first content object.

A system according to any of the points 13 to 16 wherein at least one of the navigation controls is selected from navigation controls for up, down, left or right.

A system according to any of points 13 to 17 wherein at least a portion of the first plurality of content objects is displayed at the same time with the first content object.

A system according to any of points 13 to 18 wherein at least a portion of the second plurality of content objects is displayed at the same time with the first content object.

A system according to any of points 13 to 19 wherein part of the first or second plurality of content objects are displayed with graphical indicia indicating which navigation controls are thereby available.

A system consisting of a system according to one of points 13 to 20 and one or more content objects arranged and / or selected with a system according to one of points 13 to 20.

A system for displaying and navigating multiple data streams, comprising: a video screen that defines a video screen surface; a control interface operably coupled to the video screen and configured to provide a plurality of directional navigation controls to sequentially move a user-selectable sub-area within the video screen surface in one or more directions; and a graphics engine for receiving command signals associated with one of the navigation controls to start a presentation of a primary content object from a first plurality of content objects arranged according to predetermined criteria.

23. The system of item 22 wherein the first plurality of content objects are arranged in a predetermined order of increasing or decreasing emotional motivation of a viewer to select the content objects.

The system of point 23 wherein selecting a navigation control associated with a first direction starts a presentation of the primary content object with at least the same or increased emotional motivation than a previously presented content object.

25. The system according to item 24 wherein selecting a navigation control associated with a second direction, opposite to the first direction, starts a presentation of the primary content object with at least the same or reduced emotional motivation than a previously presented content object.

26. The system according to item 22 wherein the first plurality of content objects were previously arranged in chronological order.

27. The system of item 26 wherein selecting a navigation control associated with a first direction starts a presentation of the primary content object with a prior chronological value than a previously presented content object.

28. The system according to point 27 wherein selecting a navigation control associated with a second direction, opposite to the first direction, starts a presentation of the primary content object with a later chronological value associated with it than a previously presented content object.

The system of any of points 22 to 28, wherein the graphics engine is configured to display at least a portion of the first plurality of content object data streams at the same time as displaying the primary content object data stream.

30. The system of item 29 wherein the portion of the first plurality of content object data streams is displayed with graphical indicia indicating which directional navigation controls are selectable thereby.

The system according to any of points 29 to 30 wherein the portion of the first plurality of content object data streams is displayed with graphical indicia indicating the price associated with its selection.

The system according to any of points 29 to 31 wherein the primary data stream data content is displayed with graphical indicia indicating an authorization status associated with its selection.

33. The system according to any of points 29 to 32 wherein the primary data stream with content objects is displayed with descriptive information thereof.

The system of any of points 29 to 33 wherein the first plurality of content objects are arranged in a predetermined order according to the price associated with their selection.

35. The system of item 34 wherein selecting a navigation control associated with a first direction starts a presentation of the primary content object at no cost associated with its selection.

36. The system of item 35 wherein selecting a navigation control associated with a second direction, opposed to the first direction, starts a presentation of the primary content object with a price associated with its selection.

The system of any one of points 29 to 36 wherein a control interface is further configured to provide a plurality of controls to provide explicit feedback in the form of negative or positive emotion toward the primary content object or metadata that associated with this.

38. The system of any of points 29 to 37 wherein a control interface further comprises a plurality of color-coded controls that can be used to socially share the link to the primary content object with the appropriate social network or to provide a gift to the author (s) of the primary content object or its recommender.

39. The system according to any of points 29 to 38, wherein the control interface further comprises accelerometers for detecting horizontal, vertical and other motion patterns for use as navigation and selection commands.

40. The system according to any of points 29 to 39 wherein the graphics engine is further configured to display on the video screen third-party images that have recommended content, the images presented in a row relationship with a recommender of the primary content object.

41. The system according to any of points 29 to 40, wherein the system further comprises one or more virtual channels in which content objects come from single or multiple sources, external to the recommendation system, and can be arranged in any of the following categories: recommended content, guided content, third-party content, personal library content, user-generated content and images, mail, posted content and offline viewing of any of previous or regular channels.

The system of any one of points 29 to 41 wherein the control interface is further configured to navigate between content objects arranged in dimensions and wherein the dimensions are logically nestled at multiple levels.

43. The system according to point 42 wherein the control interface is further configured to navigate between either a chronological arrangement of chronologically ordered content objects, or a vertical anxiety / desire dimension.

44. The system according to any of points 29 to 43, wherein the control interface is further configured to provide a command, a channel pointer or a display icon to access, and immediately present, as a primary content object, instructional materials relating to various functions and procedures associated with the system.

45. A system consisting of a system according to one of points 22 to 44 and a content object presented and / or selected with the aid of a system according to one of points 22 to 44.

46. A method for distributed delayed content streaming comprising: a. Providing a network-accessible memory for storing content that represents a first program; b. receiving in the network-accessible memory portions of the first program from a plurality of viewers that access the first program from another source; c. editing the portions received from the plurality of viewers in the first program; and d. upon receipt of a request from one of the plurality of viewers, forwarding the first program to the requesting viewer.

wherein the portions of the first program are received asynchronously from the plurality of viewers; wherein the first program is accessible to the plurality of viewers from the other source during a first period and wherein the first program is forwarded to the requesting viewer during a second period not identical to the first period.

47. A system for distributed delayed content streaming comprising: a. A network-accessible memory for storing content representing the first program; b. a network interface for receiving in the network accessible memory at least portions of the first program from a plurality of viewers having access to the first program from another source; c. a combination engine for mounting the portions received from the plurality of viewers in the first program; and d. a streaming interface for sending the first program to one of the plurality of on-demand viewers.

48. A system consisting of a system according to point 47 and one or more programs suitable for a system according to point 47.

49. A method for distributed uploading of content comprising: a. Determining which of a plurality of content programs are accessible from a first source for downloading to a viewer system; b. requesting to download at least a portion of accessible programs from the first source to the viewer system at a first time; c. uploading at least a portion of the accessible program received by the viewer system to a second remote source together with permission indicia to identify the viewer system; and d. requesting to download the accessible program from the second source to the viewer system at a second time different from the first time.

50. A system for distributed uploading of content consisting of: a. A viewer system functionally linked via a network to a first source of content programs; b. program logic to determine which of a plurality of content programs are accessible from the first source and to request downloading of at least a portion of accessible programs from the first source to the viewer system at a first time; and c. program logic for uploading at least a portion of the accessible program received by the viewer system to a second remote source together with the permission indicator for identifying the viewer system; and d. program logic for requesting downloading the accessible program from the second source to the viewer system at a second time different from the first time.

51. The system of point 49 further comprising: e. program logic for receiving streamed download of a part of the accessible program from the second source, wherein the streamed download part of the accessible program received from the second remote source is greater than the uploaded part of the accessible program transferred to the second source remotely from the viewer system.

52. A system consisting of a system according to one of points 50 or 51 and one or more content programs suitable for a system according to one of points 50 or 51.

53. A method for distributed delayed streaming of content, comprising: a. Providing a network-accessible memory for storing content that represents a first program received from a source; b. receiving, in the network-accessible memory, permission indicia identifying a plurality of viewers having access to the first program from the source; and c. upon receiving a request from one of the plurality of viewers, verifying the permission indicia to determine whether requesting viewer has authorized access to the program; and d. forwarding the first program to the requesting viewer after verification of the permission, wherein the first program is accessible to the plurality of viewers from the source during a first period and wherein the first program is forwarded to the requesting viewer during a second period not identical to the first period.

54. A system for distributed delayed streaming of content, consisting of: a. A network-accessible memory for storing content that represents a first program received from a source; b. a network interface for receiving in the network-accessible memory of permission indicia for identifying a plurality of viewers having access to the first program from the source; c. a check engine for determining, upon receipt of a request from one of the plurality of viewers, whether the requesting viewer has authorized access to the first program; and d. a streaming interface for sending the first program to the requesting viewer after verification of the admission.

55. A system consisting of a system according to point 54 and one or more programs suitable for a system according to point 54.

56. A system content selection and viewing system, comprising: a. A first user interface operably linked to the composition of selectable and viewable content objects for presenting substantial visual, non-textual information; b. a second user interface operably linked to the data associated with the content objects for presenting substantial textual information; c. a third user interface functionally linked to the composition of selectable and viewable content objects and the meta-data associated with the content objects for presenting visual content or textual information; and d. a network-accessible memory for storing at least a portion of the meta-data associated with the content objects.

57. A system consisting of a system according to point 56 and one or more content objects suitable for a system according to point 56.

58. A method for selecting and viewing program content, comprising: a. Providing a first user interface operably linked to the composition of selectable and viewable content objects for presenting substantial visual, non-textual information; b. providing a second user interface operably linked to meta-data associated with the content objects for presenting substantial textual information, and c. providing a third user interface operably linked to the composition of selectable and viewable content objects and the meta-data associated with the content objects for presenting visual content and textual information; and d. storing in a network-accessible memory of at least a portion of the meta-data associated with the content objects.

DESCRIPTION OF THE FIGURES

With respect to Fig. 1A, the left active right and the passive 300 are shown in the top left corner, respectively; active left and right 301; right active and left passive 302; right and left passive 303. The i axis at 12h shows angry 304, passionate 305, dominant 306, relaxing 307, bored 308, apathetic 309, care 310, panicked 311.

Figure 1B has the same designation in a square profile, the axes representing the positive emotions 314 in the horizontal axis, and the negative emotions 315 in the vertical axis ranging from layer 313 to high 312.

Figure IC shows the Anxiety vector 316 on the y-axis and the Desire vector 317 is indicated on the X-axis.

Figure 1D shows transformation of the positive quadrant in the complex plane to the logarithmic state space in accordance with the current document.

Figure IE shows the Anxiety 316 and Desire Ratio 317 in a pie chart. Figure 1H shows the same in a square diagram.

Figure 1G shows the light incidence 318 in the eyeball 319 via the pupil 320 and the retina 321.

Figure II illustrates the active left cortex 322, the active right cortex 323 and the para limbically active system 324.

Figure IJ illustrates the stable emotions that flow from anxiety 316 and desire 317. These are the higher 312 emotions such as panic 311, angry 304, passionate 305, dominant 306, and relaxing 307. The lower 313 emotions are apathetic 309 , concerns 310 and boredom 308.

Figure IK shows on a pie chart where the above emotions lie in the brain. In the left active right passion 300, left and right active 301, active right and left passive 302, right and left passive 303.

Figure 1L shows the same emotions in Mood Square. It indicates which positive 314 and which negative 315 emotions are and whether they are located high 312 or low 313.

Figure 1M indicates a number of variations on the Mood Disk. It involves the following emotions: smug 1, amused 2, angry and annoyed 3, ashamed 4, bored and annoyed 5, calm / zen 6, cheerful 7, confused 8, curious 9, depressed 10, excited 11, frustrated 12, guilty 13, indifferent 14, jealous 15, recognized 16, restless 17.

Figure IN indicates the challenge 325 on the y-axis. On the x-axis you will find skill level 326. The emotions consist of anxiety 327, excitement 328, flow tracking 329, control 330, relaxation 331, boredom 332, apathy 333, anxiety 334.

Figure 2 shows the same emotions on a pie chart where you find the fear vector 316 on the y-axis and the Desire vector 317 on the x-axis.

Figure 5 illustrates the theoretical effect of a desired TV user interfacing, including example values for the Fear coordinate f, the Desire coordinate d, the mood Ψ and the motivating force m in the Mood disk. You also see respectively left active right passive 300; active left and right 301; right active and left passive 302; right and left passive 303.

Figure 6A shows approximately the same as Figure 6.

Figure 6B theoretically illustrates the sales paths of desire based on B2B sales, fear-based B2B sales and B2C sales on the Mood Disk. It's about the emotions panic 311, angry 304, passionate 305 dominant 306, relaxed 307, bored 308 , apathetic 309, worried 310 and panic 311.

Figure 6C shows the same as Figure 6C but with the numbered phases.

Figure 6D again shows the same but the emotions are marked passionately 305, dominant 306 and relaxation 307.

Figure 7 illustrates this Flow Chart with the following elements back: 30. Public WAN; 31. Private network; 32. Viewer system; 33. Viewer system34. Content provider; 35. Modeling system; 36. Content provider; 37.

Content provider.

Figure 8 again shows a Flow Chart with the following elements: 40. Behavioral model color; 41. Modeling engine; 42. Arrangement application, 43. Network interface; 44. Gate; 45. Port; 46. Viewer system; 47. Content objects; 48. Channels / arrangement.

Figure 9A shows a Flow Chart with the following elements: 32. Viewer system 41. Neuropsychological modeling engine 42. Arrangement application; 46.

Viewer model 47. Content object 48. Channel / group arrangement 49. Behavior model 60. Indexed content material.

Figure 9D shows you the following elements on the Flow chart: 32. Viewer system 41. Neuropsychological modeling engine 42. Ranking application; 46. Viewer model 47. Content object 48. Channel / group arrangement 49. Behavior model 60. Indexed content material.

Figure 9B On the flow chart you will find from top to bottom: 61. Behavioral event 62. Channel to be changed Model 63. The channel to be used. Data to create a query from indexed content 64. Generate Ψ and m values for the local content object. 65. Ψ can channel be selected? 66.More channels 67. The next channel.

Figure 9E On the flow chart it says from top to bottom: 61. Behavioral event 62. Change the viewer model 63. Change the channel model.

Figure 9F From the top to bottom on the flow chart: 63. Query indexed content based on viewer and channel model 64. Generate F and D coordinates for each found content object 65. Assign selectable content objects to selected channels. 66. More channels? 328. Post process step for content objects without channels or discovering new clusters 67. Next channel 68. Arrange and sort objects in selected channel.

Figure 9C On this flow chart you will find: - Get the following content object 73 - More content objects 71.

Figure 10 A contains the following elements from top to bottom: - Viewers ID / network address - caption type / level - Gender / age / marital status - Genre preference 1 - preference value - Genre preference 2 - preference value

- Preference N, preferred type N, preferred value N

- Last specific request / date Average watched time - Event / date / action / elapsed time - Event / date / action / elapsed time

Figure 10 A1 contains the following table:

Anxiety coefficient ontology component 1 Anxiety coefficient value

Anxiety coefficient ontology component 2 Anxiety coefficient value

Anxiety coefficient ontology component ... Anxiety coefficient value

Anxiety coefficient ontology component N Anxiety coefficient value

Desire coefficient ontology component 1 Desire coefficient value

Desire coefficient ontology component 2 Desire coefficient value

Desire coefficient ontology component ... Desire coefficient value Desire coefficient ontology component N Desire coefficient value

Content identifier 1 Identify value

Exception Mood Disk area 1 Relaxed / passionate value

Content identifier 2 Identify value

Exception Mood Disk area 2 Relaxed / passionate value

Content identifier ... Identify value

Exception Mood Disk area ... Relaxed / passionate value

Content identifier N Identify value

Exception Mood Disk area N Relaxed / passionate value

Figure 10B shows a flow chart with the following components: o channel ID network address

o Viewers ID network address Group 101, Group IOZ, ..., Group IDM

o last modified / counting object o Dominant preference 1 - preference value o Dominant preference 2 - preference value o Dominant preference N - preference value o Subdominant preference 1 - preference value o Subdominant preference 2 - preference value o Subdominant preference N - preference value

o Preferred bucket 1 ID

o Preferred bucket 2

o Preferred bucket N

Figure IOC 1 contains the following concepts: o Content object ID - Data type o Content object ID memory reference o duration / series / episode o Genre / Actor lead 1 o Producer / Actor lead 2 o Date / publisher

Figure 10C1 contains the following concepts:

Content Object ID

Content object ID Memory reference

Date of broadcast

Time of broadcast

Start time of broadcast

End time of broadcast

Title

Year of production

Country of production

Main genre

Subgenre

Delivery title, delivery number

Delivery year

Director

The cast

Description

Qualification for the parent

Producer

Publisher

Pre-cataloged Mood disk area

Figure 11B shows a flow chart with the text: Send the following content object ld to the server.

Figure 11C illustrates a flow chart with the text from top to bottom:

Start 330

New reference 331 Resolving reference 332 Retrieving Meta Data 333 Retrieving content object 334 Setting the timer 335 Stream content 336 Streaming is done 337

Deliver Meta Data and the elapsed time in the behavioral module 338

Figure 11D shows a flow chart with the following elements from bottom to top o Display the elementary content object 339 o Is the command allowed for the elementary content object? 340 o Press the channel number? 341 o Channel above / below? 342 o Arrow? 343 o Display the channel associated with the pressed channel number 344 o Display the channel associated with the current channel number -1 / + 1 345 o Double press? 346 o Press once? 349 o Double press left / right 347 o Arrow up / down 351 o Arrow left / right 350 o display nested dimension of the primary content object i, j 348 o Channel with one source of recommendation? 352 o Display of the content object with the horizontal dimension il / + l and the vertical dimension j as elementary content object 355 o Display of the content object with the horizontal dimension Ï-1 / + 1 and and the vertical dimension jl / + l as elementary content object 353 o Representation of the demension of the content object of the recommendation source -1 / + 1 354

Figure 12C shows the following information:

Content object ld - channel / group ID Content object memory reference Ranking value / Position value Inhbud object Meta Data site references link 1 / link 2 /.../ Link N

Figure 10B1 shows another Channel ID table

Filter 1 Filter value

Filter value Filter N Filter value

Anxiety coordinate Anxiety value

Desire coordinate Desire value

Cut-off type Type value

Cut-off Cut-off value

Sort field Sort field value

Sort order Sort order value

Figure 13A shows a Flow Chart with the following information from left to right: Content file source 36, download content file / meta data 356, viewer system 32a, 32b, 32c, 32n, upload a fractional file with meta data 417, model system 35 , download the entire content in a selected format 357.

Figure 13B shows another Flow chart with the following information from left to right: Content source 36, viewer system 32a, 32b, 32c, 32n, modeling system 35, meta data / authorization indicia download 358, upload of meta data structures 359, download of the full 360 content.

Figure 13C shows a flow chart with the information from top to bottom:

For each content object of a recorded request 361

Energize against a content source provider 362

Are the access rights ok? 363

Tune to channel stream 364

Define the content object fraction 365

Change to the requested request 366

Create a data structure with meta data 367

Upload meta data and (if necessary) part in the modeling system 368

Figure 13D shows a flow chart with information from top to bottom: Content request from the viewer system 370 Is the content available? 371

Is the viewer system authorized to view the content? 372 Stream the content to the viewer system 373

Figure 13E shows a flow chart with information from top to bottom: Meta data content object and part of the viewer system 374 Update the proxy of the viewer system 375 Check the content. Is the clause useful? 376 Upde the content together 377

Figure 15 is a list with the following content:

122A: Content Object ID

124A: temporary / sequential markers 126A: Authorization indicia

128A: Channel ID

127A: Viewer's ID

129A: Description keys

Figure 17 shows a table with the following information:

Content object ID / link Link / Link

Start address / size License status / duration Recommender / image Composite system Graphic parameters Links

Figure 23 shows a diagram with the words: 34. Content source, 35. Recommendation system, 32A & B. viewer system, 36. Content source, 31. Content source

Figure 24A shows a diagram with content: content source 162a, 162b, 162n, recommendation system 35, local storage 193, graphic engine 115, screen 120, virtual recommendation channel 500, viewer system 32.

Figure 24B consists of a Flow Chart:

For every social media website on which the viewer is registered 380

Check the recommendations with viewer 381 for each social account that is linked to viewer registration 382

Collect recommendations from social accounts 383

Is the recommended content available? 384

Save the recommendation meta data and refer to the recommended content in the good channel 385

Figure 25 is also from a Flow chart. From bottom to top are the following terms: Content sources 172a, 172b, 172n, recommendation system 35, left brain screen, local storage 193, graphic engine 115, screen 120, virtual director channel 170, right brain screen, viewer system 32.

Figure 26A is a flow chart with the following concepts: 182a. Remote application, 182b. Remote application, 182n. Remote application 183. Content source, 35. Recommendation system, 115. Graphic engine, 180. Virtual third party channel, 32. Viewer system, 120. Screen

Figure 26B is a flow chart with the following information:

Receive / collect content from a third party application 386.

Is the content eligible for the right brain? 387

Save the content meta data and (refer) the content to the appropriate channel 388.

Figure 27 is a flow chart with the following concepts: 197. External storage; 35. Recommendation system, 115. Graphic engine; 193. Local storage; 120. Screen; 32. Viewer system; 190. Virtual library channel

Figure 28A contains the following elements: 204. External source; 35. Recommendation system; 115. Graphic engine; 204. Local storage; 32. Viewer system; 120. Screen; 200 virtual off-line channel Figure 28B consists of the following concepts:

Collect the selected content for offline mode 389.

Is the content eligible for the offline mode? 390 Convert the content to use in offline mode 391.

Save the content for offline access 392.

Figure 29A shows a flow chart with the concepts: 212a / b / n. Content storage; 213. External source; 35. Recommendation system; 115. Graphic engine; 120. Screen; 32. Viewer system; 216. Local storage; 210. Virtual photo / UGC channel

Figure 29 B consists of a Flow Chart with the following information:

For every social media website where the viewer provides information 393 Collect the information provided 394.

Is the content suitable for the right hemisphere? 395

Save the content meta data and (refer) the content to the appropriate channel 396.

Figure 30A consists of a flow chart such as 29A but with these concepts: 222a / b / n. Content storage, 223. External source, 35. Recommendation system; 115. Graphic engine; 120. Screen; 32. Viewer system; 220. Virtual mail channel

Figure 30B shows a Flow Chart with the following concepts:

For every social media website on which the viewer registered 397 View what the viewer has posted 400.

For every social media account that is linked to the viewer registration 398 Collect messages from the social account 399 is the post suitable for the right brain hemisphere? 401

Save the post meta data and (refer to) the content in the appropriate channel 402.

Figure 31A shows a Flow Chart with the following components: 232a / 232b / 232n. E-mail processes; 233. External source, 35. Recommendation system; 115. Graphic engine; ; 120. Screen; 32. Viewer system; 230. Virtual mail channel

Figure 31B contains the following components:

For each of the viewers' electronic mail service 403 Get the messages from the electronic mail service 404 For each message 405

Appendix with content of the type suitable for the right hemisphere 406

Retrieve the meta data messages and save the meta data, the content and the most important point at 407

Figure 33. Shows a Flow Chart with the following information from bottom to bottom:

Colored button? 408

Red button? 409 Update the viewer model based on this content object and / or its meta data 410

Blue button 411 - □ Update the viewer model based on this content object and / or its meta data 412

Yellow button 413 - □ Post a link on the content object to apply to the social network 414

Green button 415 - □ Register the viewer's gratitude for applicable author / recommendation of this content object 416

Figure 34. Shows a Flow Chart with the information: 1. Begin emotion 2. The will to change 3. Private fear covered 4. Social fear covered

The arrows on the arrows say round the clock: o Desire is nurtured o The private fear is being covered o The social anxiety is being covered o Desire gives satisfaction

Figure 34. Shows a Flow Chart with the information: 1. Begin emotion 2. The need to be recognized 3. Private fear covered 4. Social fear covered

The arrows say clockwise: o Fear is created o The private fear is covered o The social fear is covered o Desire gives satisfaction

Figure 34. Shows a Flow Chart with the information: 1. Begin emotion 2. Private fear covered 3. Social fear covered

The arrows state clockwise: o Desire is nurtured / Private fear is covered o Social fear is covered o Satisfaction

Figure 37. Shows a Flow Chart with the following components: 60A. Purchase offer; 41A. Neuropsychological modeling engine; 46A. Purchase models 42A. Ranking application; 49A Behavior modeler; 48A. Ranking / sales channels; 47A. Sales items

DETAILED DESCRIPTION

Unless defined otherwise, all terms used in the description of the invention, including technical and scientific terms, have the meaning as generally understood by those skilled in the art of the invention. For a better assessment of the description of the invention, the following terms are explicitly explained.

"A", "de" and "het" in this document refer to both the singular and the plural unless the context clearly assumes otherwise. For example, "a segment" means one or more than one segment.

When "about" or "round" is used in this document for a measurable quantity, a parameter, a duration or moment, and the like, variations are meant of +/- 20% or less, preferably +/- 10% or less, more preferably +/- 5% or less, even more preferably +/- 1% or less, and even more preferably +/- 0.1% or less than and of the quoted value, insofar as such variations of are applicable in the described invention. However, it must be understood here that the value of the quantity at which the term "about" or "round" is used is itself specifically disclosed.

The terms "include", "comprising", "consist of", "consisting of", "provided with", "contain", "containing", "include", "including", "contents", "contents" are synonyms and are inclusive or open terms indicating the presence of what follows, and which do not preclude or preclude the presence of other components, features, elements, members, steps, known from or described in the prior art.

The citation of numerical intervals by the end points includes all integers, fractions and / or real numbers between the end points, including these end points.

Neuropsvcholoaic Model: Mathematical Modeling Emotions

Proposed herein are specific characteristics of parallel human thinking in the left and right cortex, including a proposal for the explanation of the underlying mechanism of neurotransmitter. Positive and negative human emotions are defined and the bivalent of emotions are represented under this definition. The proposed mathematical independence of positive and negative emotions is supported by their largely independent physiological constitution. This forms the basis for the mathematical classification of emotions and moods in a two-dimensional emotion space. Individual forms of consciousness are defined and an explanation of how the mood arises from consciousness is provided. The moods are well described in a logarithmic complex emotion plane, formed by two perpendicular dimensions, the expression of natural anxiety and desire components.

Emotions are bivalent instead of bipolar. Based on the above definition of positive and negative emotions and considering their independence or mathematical squareness, emotions can be modeled in two perpendicular dimensions, rather than in a dimension where the positive and negative emotions would be negatively correlated.

Therefore, positive and negative emotions can be represented as two independent or perpendicular basic vectors in mathematical emotion space, thus decomposing every emotion into its positive and negative emotions components, represented in a two-dimensional domain, where the emotions can be represented as vectors, coordinates or real and imaginary parts of complex numbers, as shown in Figure IC. Dissecting emotions into their natural anxiety and desire components Anxiety is defined, with capital 'F, not just as fear, but as the general negative elemental emotion. By analogy, Desire is a general positive valence elemental emotion. Although there is an alternative to naming it, it provides an intuitive understanding of more abstract mathematics. Representation of moods in this two-dimensional Anxiety - Desire domain causes mathematically dissolving every specific emotion in its natural components of Anxiety, intuitively understood as fear and desire, intuitively understood as desire.

Such decomposition into basic emotions by projection on the perpendicular vector basis (Edl, Efi), where | Ëdl | = 1 and | Efi | = 1 is mathematically represented as: E = Ed + Ef = x * Edl + y * Ëfi

In this comparison, E is a vector with size | E || = E and direction φ (see figure 3). Using complex annotation numbers, the desire part is the real part of the complex emotion z, fear is an imaginary part.

z = x + i * y = d + i * f D and F are the Desire and Anxiety coordinates represented as (d, f) of a specific emotion. They are the result of projecting the emotion on the orthogonal basis of fear and desire and can be represented in the positive quadrant of the complex plane.

Emotions and moods are well represented in the logarithmic complex emotion plane. The emotion and mood space can be represented as the positive quadrant of the complex plane, where (1.1) stands for the individuals average level of anxiety and desire. Using the logarithmic representation of mental states, this emotion space can be transformed into a mood space that covers the entire complex plane, where 0 is assigned to - oo, 1 to zero and + co to + oo, because exp (- co ) = o, exp (0) = 1 and exp (+ oo) = + oo.

Therefore, moods can be displayed in the complex logarithmic mood plane of Figure 1D.

Representing Emotions In The Mood Disk

The complex plane represents the emotional domain that can be mapped onto Mood Disk disk. To represent this complex logarithmic mood area in a more compact way, without using the notion of infinity, we represent moods on a unit disk, called the mood disk, as shown in Figure IE.

To arrive at this Disk, the logarithmic complex tuning area was first mapped onto a Riemann sphere using the inverse stereoscopic projection, shown in Figure 1F. The points A and B are projected by the stereoscopic projection. With the same holographic projection, this complex plane is also projected on half a Riemann sphere with center S (oo), as shown in figure 6. A and S (A), but also as B and S (B) are projected on GS (A) and HS (B) respectively. Next, this half Riemann sphere is expected to be the unit disk as the bottom of the half Riemann sphere by projecting 0, projecting GS (A) on AMD and HS (B) on BMD. The resulting unit disk projection ensures the natural display of moods on the mood disk, without affecting the intuitively less accessible notion of infinity.

Representing emotions on the Mood Square.

Finally, emotions and moods can be naturally, intuitively and mathematically easily represented in an emotion or mood square. The linear left brain consciousness has difficulty interpreting the non-brain

Euclidean metric of the emotional disc. And confusion occurs easily if straight lines are represented non-linearly.

In the mood disk straight lines are represented as circles, except for the rays of the sensory disk and through a certain point an infinite amount of parallel lines, represented as circles, can be drawn in the mood disk, meaning that the metric is non-Euclidean .

Since the mood disc is analytically difficult to read due to the distortion caused by the stereographic projection, we can present them in a simpler or more straightforward way, more accessible to the left consciousness. We achieve this by representing the unit disk in the Chebyshev metric as a unit square, shown in Figure 1H.

This emotion and mood unit Square is accessible to both the right and left brain consciousness and therefore the desired domain to represent emotions and in fact any dimensional phenomenon on the Riemann sphere as S (A) and S (B).

Locate Sell & Buy On The Mood Disk

Referring to 5B, business-to-consumer sales figure is best done in the - n / 8 - 3 n / 8 area, while business-to-business sales can best be positioned in the / 8 + 3n / 8 space. Or, in words, sales and / or marketing will be most successful if they put the consumer in a relaxed mood and do business in a passionate mood. Indeed, fear is usually greater when one buys on behalf of a company than when one buys something as just a consumer.

Given a certain level of desire, which is represented by the desire coordinate d, Vreest represented by the fear coordinate f, can be reduced to the level that the motivational power of m is maximum or close to -n / 4 for sale to consumers or + n / 4 for business-to-business sales.

In order for a consumer to sell optimally instead of buying, one has to be localized to the - 3n / 4 atmosphere in the Mood Disk. Which means, it is usually in favor of a business / consumer to buy from a person who feels apathy towards the product that you want to buy from him. In all other cases, the selling price will often end up higher. For example, when the consumer / seller is afraid that he may still need the product or regret the sale, or when he absolutely loves the product (passionate mood), he is likely to be less willing to sell it.

In order for an enterprise to sell optimally instead of buying, a localized location must be established on the + 3n / 4 atmosphere in the Mood Disk. For example, it is usually in favor of a buyer to buy from a B2B sales person who is scared (for example, about not hitting his goal). Also it is usually to the advantage of a consumer to buy a brand, which lowered their prices because they are concerned about the competition.

Locate applications on the Mood Disk

Application of the previous model specifically for interface design / development without loss of priority in other areas of application, enables accurate modeling of user psychology.

Watching television => Relaxing mood

Figure 6A conceptually shows the effect of an unwanted TV user interface experience represented as a path on the Mood Disk starting with a relaxed mood and ending in an angry mood.

Television sales => Relaxed mood Television management => Passionate mood

Reading and researching => Relaxed & passionate mood Trading securities => Panic & passionate mood Bank / investing => Worried / Panic mood Selling => Relaxed & passionate mood

Locate platform sales on the Mood Disk

It is possible that the mood is optimal for the nature of the sale at hand, different from the Mood Disk, usually with regard to the platform at hand. As explained earlier, business-to-consumer sales are best done in the - π / 8—3 n / 8 area (relaxed atmosphere), while business-to-business sales can best be positioned in the n / 8 + 3n / 8 area (passionate mood). We also know that right hemisphere platforms such as television are usually located in the - n / 8 - 3 π / 8 area, while for example internet websites are usually located in the n / 8 + 3n / 8 area.

In general, the nature of the sale has a stronger influence on the design of a purchasing platform / process than the type of platform. This means that, for example, a business-to-consumer website for books is optimally designed in such a way that the consumer is relaxed. Reading itself, on the other hand, is something that people normally do in a passionate mood. So when it comes to reading, the optimum purchasing experience (relaxed atmosphere) differs from the optimum product experience (passionate mood).

Modeling fear and desire elements

Modeling a user's fear and / or desire component to a specific product or content can be done by collecting conscious user feedback and / or by unknowingly measuring viewing and surfing behavior while watching TV or surfing the website .

Reduction of the Anxiety component is preferably performed in a Left Brain Activity environment, such as with a text-based work environment and not, for example, while watching TV. Consequently, viewing and surfing behavior is extremely suitable for modeling the D coordinate, while the active text-based input is suitable for modeling the f coordinate.

The Television Recommender

The foregoing concepts for modeling Desire and Anxiety vectors relative to their mapping on the Mood Disk can be performed with a unique neuropsychological modeling engine as described herein. For the sake of clarity and intelligibility, we describe the operation of such a motor after the example of a television experience system. However, the principles apply to a wide range of applications, namely all those who can take advantage of recommender functionality. The modeling engine described here, for example, serves as a mechanism whereby content objects can be arranged whereby a given, (viewer) his viewing / surfing behavior is measured unconsciously and / or conscious feedback from users. Once arranged, the specialized set of user interfaces described herein can be utilized for multidimensional browsing of the previously arranged content objects.

Unique to this disclosure is the concept of a truly subjective channel. In contrast to the state of the art in which subject content is objectively classified according to the content provider source and defined according to the available viewing times. A channel in accordance with the disclosure comprises one or more groups of content objects specially selected based on a viewer's subjective preferences and mood and it is arranged in order from low to high emotional motivation for the viewer to select and select the content. see. In an exemplary system, a viewer or a group of viewers, such as a family, may have multiple personalized channels containing content programs that are autonomously merged and screened according to their personal interests, using the modeling system described herein and which can be viewed using the user interface application controls that are associated with the viewer system 32 described herein. Or they are made by mixing the individual channels.

Network Application of Recommender Engine for the viewing experience

Figure 7 illustrates conceptually a network environment 38 in which the neuropsychological modeling engine described herein can be executed. Network environment 38 includes one or more private networks 31 and a public wide area network (WAN) 30 such as the internet. Private networks 31 can be implemented with all known network technologies such as a cable package network from a cable service provider or a packet-switched local area network (LAN) or wireless network. Public network 30 may contain a coherent collection of other networks using all currently known network technology including both wireless and optical etc. Functionally linked to each of the networks 31 and 30, a content provider 34 is a viewer system 32 and a model system 35 that contains the neuropsychological modeling engine described herein. Also connected to the network 30 are additional content providers 36 and 37, as well as an additional viewer system 33. The viewer systems 32 and 33 can be implemented as described with reference to Figure 11.

Modeling system

Figure 8 illustrates a theoretical block diagram of modeling system 35 that includes the neuropsychological modeling engine 41. In particular, system 35 described in phantom consists of a pair of gateways 44 and 45 connecting system 35 to networks 30 and 31, respectively. In an exemplary embodiment, system 35 further comprises a server platform 40 and one or more databases 46-48. Server 40, which can be executed with a single server or multiple servers, runs neuropsychological modeling engine 41 and ranking application 42 and behavioral modeller 49 which all communicate with each other but also with databases 46-48 and other entities that via the network interface 43 that connects server 40 to databases 46-48, as well as networks 30 and 31.

Database 46 can be used to store documents or other data structures that represent the neuropsychological model of one or more viewers connected to the viewer system 32 as well as to store other viewer systems. Database 47 can be used to store content objects, e.g. the files of the various multimedia content, available for viewing the viewer's content 32. Database 47 can also store meta data in connection with the respective content files. Figure IOC theoretically illustrates an example of a content object meta data file 75. Database 48 can be used to store one or more channels 90A-C, which are the rankings or commands of multiple content objects associated with channel model (s), 72 and viewer model 70. Note that although each of databases 46-48 are represented as a single database, it is contemplated that one of them can be executed with a number of databases in different configurations, including distributed, redundant and peer-to-peer continuous migration of configurations . Alternatively, the data from one or more of the databases 46 to 48 can be combined into a single database. For example, can the arrangement of the content associated with a specific viewer channel model be stored together with the data defining the viewer model? In addition, each of the databases 46-48 may contain their own database server for interfacing with the server 40 or they may share a database server.

Figure 9A theoretically illustrates the elements of an embodiment of modeling system 35 needed to derive the relationship between the meta data linked to a content object and an individual viewer model relative to the arrangement of the content object in relation to the specific channel model. Specifically, each object has content stored in the database 47 with a file 75 attached to it, which has various data parameters for the content of the file, such as the format, duration, title, genre, actor, producer year of the first release, etc. contains. Any number of different data structure formats can be used for this particular structure. Such content file files can also be stored in the database 47.

Also, each individual (or group of viewers, e.g., a family) associated with viewer system 32 has one associated with it. model 70, which contains data describing the behavioral model consisting of viewers meta data such as. includes gender, age, occupation, product / service description level etc. and idealized preferences for the viewer (or groups of viewers) in terms of genre, actors, particular series, area of interest, past selection history, viewing times, duration or other parameters. Figure 10a illustrates an exemplary data structure that can be used to execute the behavior model 70 for a specific viewer (or groups of viewers). As previously noted, such viewer meta data files can be stored in the database 46.

To help with the effectiveness of their services search engines such as Google, Bing, Yahoo, etc., ontologies of reality are created. Ontologies are used in artificial intelligence, the Semantic Web, Systems engineering, software engineering, biomedical computer science, library science, business bookmarking, and information architecture as a form of knowledge representation about the world or part of it. In essence, such search engines create an objective index of the content of that reality. Such indexed content is stored in one or more databases as shown in Figure 9A by database-60. In an exemplary body, database 60 and the indexed content may or may not be part of modeling the system 35, but may therefore be accessible through a public or private network.

Numbers 9D-F illustrate the process flow between the components of modeling the system 35 into a viewer model and channel model update, retrieve new information and determine whether this content is suitable for ranking according to the system model of the viewer's emotional motivation. Referring to Figures 9E-F, viewing behavior including events such as requesting a specific program, completion of viewing a content object, saving, or purchasing content, managing a channel, causing viewer system 32 for sending event data packet (s) the behavior model 49 of modeling the system 35 as illustrated by arrow A of figure 9A and decision-making blocks 61 of figure 9E. After receiving such event data, behavior model 49, it modifies the viewer model 70 in relation to the specific viewer, as illustrated by process blocks 62A and, if necessary, channel model (s) 72, as evidenced by process blocks 62B.

Behavior model 49 then retrieves the model from database 46 for the specific viewer and the meta ata file 72A that defines the channel. In addition, behavioral model 49 extracts from database 47 the file describing the content. Thereafter, model 49 compares the received event data with file 75 of the content object and the current 70 and changes the channel model (s) 72 properly (indicated by the round arrow in model 49), as illustrated by process blocks 62A and 62B of 9E. In each case 70 is changed and possibly the channel can also be changed, as would be in case of channel management and search term change.

At certain events, e.g. periodically (a timer event), viewer event, event content (e.g., new VOD content), the modeling engine 41 is performed. The modeling engine 41 requests from database 60 an indexed content material that may be of interest as illustrated by arrow D of Figure 9D and blocks the process 63 of Figure 9F.

In this case, modeling engine 41 can be programmed to interact with the query format of a number of different sources of indexed content or content libraries.

As a first step, modeling engine 41 works based on content filtering based on and the channel model. Note that both the viewer model and the channel model are used in the illustrative embodiments to specify requests and questions. Referring to Figure 9E, queries can be based on a combination of ontology components (with strong coefficient values in model) and filter criteria from the channel Based on the coefficient corresponding to each selected component available in the model (as calculated by process block 62A) the Mood Disk disk Fear D coordinate f, and Desire D coordinate for this content object are calculated.

In embodiments, the modification of the viewer model 70 can be performed with the following algorithms. Each event is mapped on the Mood Disk disk 20 according to a prescribed rule, e.g., purchase of a content object results in a predetermined Ψ and m- value (or an equivalent Fear D coordinate f and Desire D coordinate). In a first step in the location on the Mood Disk disk 20 of the content is described, object is determined for a particular user.

It is assumed that for the viewer in question the content object is probably somewhere in the demarcated area in Figure 6D. Neuropsychological model engine 41 examines the metadata file for the content object, and in combination with metadata from the viewer's meta data file and / or channel model, calculates where on the mathematical model of human emotion, i.e. the Mood Disk disk, previously described With reference to Figures 1-6, the viewer mood and motivational power are relative to that specific content object. Based on the coefficient corresponding to each selected component available in the viewer model (as calculated by process block 62A), the Mood Disk Fear coordinate f, and Desire coordinate d for this content object are calculated ... For each channel that is associated with the viewer model ranking application 42, it assesses whether the content object meets the filter criteria for the channel. In a next step, the similarity of the mood each selected the contents of object vector to the Mood Disk vector associated with this channel calculated using the "cosine similarity measure". This measure allows the application to rank the contents of objects selected for this channel relatively based on their similarity to the channel vector's mood. In an optional second step, a "collaborative filtering" post-processing step to update the rank of the content of objects in the selection of the engine 41 for this channel and viewer. However, unlike traditional "collaborative filtering" implementations the "similarity" of viewers is calculated not only based on the desired content of objects and a correspondence in the preferred language of the content of object metadata, but also the correspondence in the Mood Disk stored in the viewer's model.

Viewer system

Figure 11A conceptually illustrates a viewer interface system 32 relative to public network 30, content provider sources 34 and 36, and model system 35 in accordance with the disclosure. Also illustrated in Figure 11A is the remote control 88 related to display 80. The viewer system 32 includes a first or right brain user interface to display 80, primarily used for viewing video content that can be used in the illustrative embodiment. equipped with a television screen 80 and a corresponding remote control 88. Display 80 can be performed with a "connected TV" or other devices that connect the TV to the networks of 30 or 31, such as a connected Blu-ray player or a game console. connected, for example a device capable of direct connection to the internet, for example the network 30, as well as a cable packet network or satellite network, for example the network 31. Viewer system 32 further comprises a second or left brain user interface 84 which a content presents surf interface and purchase interface and can be performed on a Personal Digital Assistant (PDA) or smart phone, tab let computer or even laptop computer.

This second user interface mainly uses and / or stimulates the activity in the left hemisphere of the human brain, and also, to a limited extent, the right hemisphere of the human brain. A viewer will typically use the second user interface from 84 through activities such as storage, purchasing, changing the order of, specifying an if / dislike for a particular content object within the rankings of a channel 90 from to feed. Viewer system 32 further optionally includes third and fourth user interfaces 86 and 87, respectively, capable of presenting both the textual based interfaces for content browsing and purchasing, as well as visual content and can be implemented with a traditional personal computer such as a desktop or laptop, but also other systems.

Figure 11B illustrates the algorithmic processes performed by a redirect application 85. The first, after activation, request 85 waits for remote commands sent from the remote control 88. Application 85 examines the data of a received signal, usually the field in a header file or the data stream identifying a command to determine whether the received signal associated with a command becomes one of the signals to be diverted, such as the Up, Down, Left, and Right cursor navigation signals from the remote control 88. If so, depending on the cursor navigation command, the application application 85 sends to the model system 35 the data needed to view the new content object. This data can be implemented in a number of different techniques, such as with a memory off-set at one time or recently viewed content objects, with a sequence number representing the next content object within the channel data structure 95, or with a soluble link retrieved from the file with metadata content linked to the currently displayed object, as stored locally within the viewer system.

Figure 11C illustrates the algorithmic processes being performed by the server application 51 of modeling the system 35 after receiving the handle or reference data from redirection application 85 identifying the following content object to be displayed. Depending on the nature of the handle or reference data, server application 51 unloads all addresses, links or references to the next content object to be displayed and then extracts the meta data file associated with such a content object, usually from the database 47. Then the actual data related to the content object retrieved from database 47 and to the first user interface 80 of the viewer system 35 via either public network 30 or private network 31, depending on the precise implementation of the system. Simultaneously with the start of content streamed to viewer system 32, 49 server, the application can start with a timer to determine the last time until the streaming is terminated, usually when the next content object to be viewed is selected. After receiving a command to terminate the streaming server, application 51 sends a value that elapsed time of the previously assessed content object together with the meta data of the content object behavior model module 49 for updating behavior change of the viewer model. Other available commands can similarly cause streaming of content to end and the viewer behavior model to be updated with the elapsed time, including but not limited to, channel up / down, back button (results when starting another content object), pause, fast-forward, rewind (within the content object), etc. You can, instead of maintaining an elapsed time value, server application 51 can examine the time code embedded within the header of the last streamed data packet to determine roughly how much of the content object was viewed by the viewer before the streaming was terminated. Data that elapsed time based on this value can then be sent in the same way to behavior model module 49. Thereafter, a similar process takes place for identifying, retrieving, and streaming the next content object to be viewed.

The process of using the cursor navigation buttons to perform multidimensional browsing of content objects within a certain viewer channel is illustrated with reference to 12A-B Figure. Referring to 12A, a multidimensional channel, Figure 90 has been conceptually demonstrated to illustrate the concept of multidimensional browsing of content along the desire and time vectors 92 and 94, respectively, using traditional cursor navigation buttons 91, 93, 95, and 97. In particular, channel 90 associated with a specific subject / viewer comprises a first plurality of content objects C1, C2t, C3t, C4T, C5t, ... Cnt along a first dimension 92 that were arranged in order decreasing desires usually, from high to lowest. In an illustrative embodiment, viewer activation of the Up cursor control 91 initiates viewing of the next content object in dimension 92 of channel 90 for which the subject / viewer will require increased motivation to view or purchase the content thereof . Also, viewer activation of the Down cursor control 97 initiates viewing of the next content object in dimension 92 of channel 90 where the subject / viewer will require a reduced motivation to view or purchase the content.

One or more of the first plurality of content objects Clt - Cnt are connected by links or references, a second plurality of content objects that are related by chronological order along a second dimension 94 and which share one or more common meta data parameters. For example, as illustrated, content object C4T has related a plurality of content objects C4T-1, C4T-2, C4T-3, C4T-4, ... C4T-n chronologically in a first direction, for example, sequentially in order of increasing age in the left direction. Content object C4T also has a multitude of content objects C4T +1, C4T +2, C4T +3, C4T +4, ... C4T + p chronologically in a second direction, opposite the first direction, for example, in order of descending age in the direction to the right. In an illustrative embodiment, activation by the viewer of the left cursor control 93 initiates viewing of the next object in the content to the left direction of the dimension 94 of channel 90 in which the subject / viewer will require at least the same motivation to view or buy the content. Also viewer activation of the right cursor control 95 initiates viewing of the next content object in dimension 94 of channel 90 for which the subject / viewer may also have at least the same or different motivational desire to view or purchase the content.

Distributed Upload System

The aforementioned systems can be used in combination with the distributed upload system described below. Referring specifically to Figures 13A-B, selected elements of the network environment 38, as illustrated in Figures 7, 8 and 11A, are conceptually represented. In particular, Figure 13A illustrates a plurality of systems viewer 32a-n operatively linked to both a content source 36 and a model system 35. Viewer systems 32a-n can be implemented as previously described with the additional modifications as described below. The modeling system 35 can also be carried out as previously described. Content source 36 can be executed as previously described with reference to the source 60 of Figure 9A, which contains indexed content material, or one of the content providers 34 or 37 of Figure 7, or, each of Cable TV service provider may consist of via the cable package network, satellite TV provider via the satellite network, or broadcast live via internet (internet television).

Figure 13b illustrates an alternative conceptual network configuration, similar to Figure 13A, except that content file source 30 communicates with the modeling system 35, in addition to or in place of the viewer systems 32a-n.

Figure 14 illustrates conceptually selected elements of the display system 32 interface to public network 30, content provider source 36, and modeling system 35 in accordance with the disclosure. The viewer system 32 comprises a first or right brain user interface screen 80, which is mainly used for viewing video content that can be implemented in the illustrative embodiment with television screen 80 and an associated remote control 88. Display 80 can be performed with a "connected TV" or other devices that connect the TV to the networks 30, such as a connected Blu-ray player or a game console is connected, for example a device capable of direct connection to the internet, such as the network 30, as well as a cable packet network or satellite network, for example the network 31. Viewer system 32 further comprises a second or left brain user interface 84 that presents a content surf interface and the purchase of interface and can be performed on a Personal Digital Assistant ( PDA) or smart phone, tablet computer or even laptop computer.

In the embodiment for clarification, television screen 80 further comprises a request process 100 for interface with content provider source 36 and modeling of the system 35. In particular, the application comprises 100 includes modeling of interface process 102 and crawler process 104. Modeling of system interface process 102 makes viewer system 32 through source 36 and modeling system 35 communicate in a manner described below with reference to Figures 13A-B. Crawler process 104 cooperates with process 102 and content source36, and, if applicable, a scheduling application or electronic program guide function 106 related to content source 36 in a manner described below.

Crawler process 104 interacts with content source 36 and model system 35, via process 102, in the following manner. Crawler continuously processes 104 searches scheduling function 106 in relation to content source 36 to determine which content programs are currently accessible for download streaming from content source 36 through to viewer system 32.

The determination of such accessibility will usually be determined by registering the viewer with the content source provider. Every time process 104 identifies content that the viewer has legally authorized access, crawler process 104 initiates download streaming of content to display 80 and buffers a fractional percentage of content in memory associated with display 80 further along with selected metadata linked to content, including the data identifying the content, and one or more temporary or sequential identifiers or markers identifying the specific portion of the content contained within the buffer, as illustrated by arrow A of Figure 13A. Figure 13C shows a conceptual algorithmic processes to capture and upload content object fractions y-viewer system 32. Crawler process 104 then sends to process 102, one or more packets of data regarding the buffe content together with the information identifying the content. Or, alternatively, it offers the addresses in memory where this information is stored and accessible by both processes. Process 102 adds to this information, a data structure 120 as illustrated in Figure 15 and transmits or streams such information to the model system as illustrated by arrow B of Figure 13A. In one embodiment, process 102 may request composition server 110 from the viewer model or determine whether a full copy of the content object already resides in the aggregation server database 112 or database 47. If so, process 102 will only send the data structure 120 to the aggregation server 110 to eliminate unnecessary network bandwidth usage. If aggregation server 110 requires a specific segment of the content object, the process 102 will specify the specific segment (s), recognizable by temporary or sequential identifiers process. Process 102 will process this information to crawler 104 for forwarding and acquiring the content from / to the source 36.

Referring to Figure 15, in one embodiment, data structure 120 may consist of the identification data of a portion of a content object 122, temporary or sequential identifiers are associated with the content object 124, 126, and authorization indicia to identify a viewer process. Thereby, data structure 120 may further consist of possibly the data 128 identifying a user-defined channel in connection with the viewer process and identification data of an encryption key 129 for decoding the content object.

The functionality repeated by crawler processes 104, while the continuous display device 80 is further functionally connected to content source 36, for all content processed by the viewer.

User interface for Presentation and surfing of multiple content objects

According to one aspect of the disclosure, a system and technique for presenting multiple, simultaneous content object data relies on a user interface that is provided in a way that the viewer surfs in multiple dimensions. A primary content stream, representative of the selected content object in a dimension of a viewer channel, is presented in a substantial part of the right brain user interface screen area while a plurality of secondary content object data streams, representing selectable content objects on which the viewer can navigate, are presented in smaller or thumbnail format in the balance of the user interface display area. The multiple secondary content streams presented on the user interface each represent selectable content objects with a queue relationship to the selected primary content object data stream. Such a queue relationship can exist between and between different content object streams in the same dimension of a viewer channel or between separately selectable parts of a single object content stream or program, or between different content objects in these dimensions of a viewer channel, e.g. chronologically arranged episodes from the same program.

The process of using the cursor navigation buttons to multidimensionally browse content objects within a particular viewer channel is described herein with reference to Figures 12A-B. Figure 12A conceptually illustrates a multidimensional channel 90, which multidimensionally surfing the content along desire and time vectors 92 and 94, respectively, using traditional cursor navigation buttons. Fig. 12B conceptually illustrates the implementation of channel 90 associated with a specific subject / viewer in the database 48. Channel 90 may consist of a plurality of channels 90A-C stored in the database 48 of model system 35.

The process by which navigation controls can be used to surf multidimensionally and view the content object streams displayed on viewer system 32 within a particular viewer channel 90 is described with reference to Figs. 16-22 referring to Fig. 16, database 48 of the model system cooperates with content database 47 or other content sources 34, 36 to ensure that a data stream containing the content object (s) within viewer channel 90 is buffered in memory associated with viewer system 32 for rendering and viewing on the Viewer- interface 32 consists of the right brain user interface screen 80, which is mainly used for viewing video content and an associated remote control 88. Figure 16 illustrates conceptually of the relationship between the components of the screen 80 (in phantom), including User Interface (UI) display area 120, 115 graphic engine, a primary stream buffer 116 and multiple secondary stream buffers 118 A-n related to the content objects, consisting of a viewer channel. Graphic engine 115 is typically part of the display 80 and controls the streaming, decoding, windowing, and display of multiple data streams based on the content data and command / format data contained in the data packets associated with each stream. Buffers 116 and 118 can be implemented as segmented sections of the local memory associated with graphic engine 115, or else they can be separately and remotely stored from screen 80. Display 80 and viewer system 32 are connected via the network 30, represented as a cloud in Figure 16, the model system 35 and the source of the content object data streams, usually one of the database 34, 36, 37 or 47. A multitasking / multithreading control system can be used in the viewer system 32 for streaming, buffering and monitor display of content object data stream.

Specifically, each stream may be associated with different threads of execution, including a thread for buffering and one or more threads for formatting and displaying content object data on the display of the display 80. As illustrated in Figure 16, the location where content stream object has a buffer 116 attached to it and one or more threads, collectively referred to as 117. The plurality of secondary content object streams each have a perspective buffer 118 An and associated sets of one or more threads, collectively referred to as 119a -n, as illustrated. In the described embodiment primary content object data stream 128 is streamed from the original source through the respective buffer while the secondary content object data streams 121 to 126 can optionally loop through part of their respective content, usually the first few minutes or another amount stored in each of the respective buffers. In this way, the presentation of visual information to the viewer on the UI display 120 is more informative, particularly regarding secondary content object data streams 121 to 126, efficient use of resources within the processor graphic engine 115 and network bandwidth in and from viewer system 32.

Each content object with data streamed up to and including screen 80 has associated therewith a data structure 111, as illustrated in Figure 17, which includes information regarding the visible parameters of the content object, including but not limited to layout parameters, status, navigation Options and Property Rights Data. In addition to the metadata concerning the content object, such as the object identifier, the format identifier, links to other content objects within the viewer channel, the memory address where the data consists of the saved object and the size of the content object, data structure 111 also exists from data fields indicating the license status of the object, whether or not free (prepaid), pay-per-view, or pay for one-time use, view elapsed time, whether the content object was compiled by the model system 35, the name and the photo of the person who recommended the content object, and other data necessary for the representation of the different graphic elements and instructions around the representation of the content object, as explained in more detail in figures 18 - 22. Virtual channels

Referring to Figure 23, a plurality of virtual channels 160-230 are conceptually illustrated with respect to viewer systems 32a-b and a model as described herein, and other sources of content. Virtual channels 160-230 make it possible to have objects from left-brain half content content being implemented in a right-brain half user interface in accordance with the objectives of the disclosure. Virtual channels 160 to 230 can be logically controlled similar to channels 90A-C of Figure 12B and can contain content objects from a single source or multiple sources, as described in more detail in numbers 24-31.

Referring to Figure 24, a first type of virtual channel, Recommendation Channel 160, may include posting recommendations from friends and / or family or other individuals from other sources, such as Twitter, Facebook, Picasa, Vimeo, groups within Facebook, Linkedln, or a other website or network mechanisms 162a-n to model for display via the viewer system 32 32.

Referring to Figure 25, a second type of virtual channel, a Program Director Channel 170 can explicitly (left brain) take control of the experience of viewing session and active control of the content of that channel.

Director Channel 170 can be useful for viewers who love film, viewers who want to schedule a specific viewing session, professionals who want to schedule a specific presentation sequence, such as a demo for a client.

Explicit viewer feedback

In addition to the implicit feedback detectable by viewer's selections and viewing behavior, the described system also offers the possibility of giving explicit feedback to the recommendation system in a manner that requires little left brain activity. In particular, traditional navigation controls from the display remote controls, for example specifically colored coded controls, can be used to give explicit feedback to the recommendation system in a manner that requires little left brain activity. Selection of different color-coded keys can be used to involve any of a negative or positive valence emotion in the cases of a certain periodically broadcast content (e.g., a series) and / or its metadata. In addition, the selection of another color-coded check can be used to share socially on the current content of the applicable social networks or to give a reward to the author (s) of the content currently being viewed or the recommender of that content.

Specifically, as part of the disclosed system and technique for relaxed TV viewing, the command 240-246 controls a typical remote control 88 or be another device that receives new functions as illustrated in Figure 32.

As illustrated in Figure 32, the selection of a first colored control panels 240, e.g., of a red button, can be used to involve negative valence emotion in the cases of a particular periodic broadcast content (e.g., of a series) and / or its metadata.

Selection of a second colored control 242, for example of a blue button, can be used to associate positive valence emotion with the cases of a certain periodically broadcast content (for example of a series) and / or its metadata.

Selection of a third colored control 244, for example of a yellow button, can share socially to the current viewed content of the applicable social networks.

Selection of fourth colored check 246, for example of a green button, can convey gratitude to the author (s) of the content currently being viewed or to the recommender of that content.

It will be apparent to those reasonably skilled in the art of the variations of the system described above and the technique used. For example, there is no need to provide a specific one to a correspondence between checks and the type of explicit feedback from the viewer on the recommendation system.

Although the various embodiments of the system and techniques described herein with reference to the content objects with video data, the system described, in particular the tandem user interface and the neuropsychological models engine can also be used with other forms of content, including audio, art, advertising, literature, physical objects, etc. with only minor adjustments to the described system and techniques as would be understood by those reasonably skilled in the relevant art, given the disclosures as described herein.

It will be apparent to those who are reasonably skilled in the art that changes to the systems and processes described herein may occur without departing from the true spirit and purport of disclosure. For example, any two elements that are directly connected or via a network can use either a push or a pull technique in addition to a specific communication protocol or technique described herein. Furthermore, despite the network implementation described, any existing or future network or communication infrastructure technologies can be used, including any combination of public and private networks. In addition, although specific algorithmic flow charts or data structures have been illustrated, these are merely exemplary purposes, other processes that obtain the same functions or use different data structures or formats are considered within the scope of the terms described herein. As such, the exemplary embodiments described herein are for illustrative purposes and are not intended to be limited.

The following paragraphs are the conclusions as included in the original patent application no. BE2011 / 0617 filed on October 21, 2011.

A recommendation system functionally linked to a network-accessible source of the indexed content objects and a viewer system, the recommendation system capable of modeling the buyer / buyer psychology, the recommendation system comprising: a. A neuropsychological modeling engine, functionally linked to the network accessible source of indexed content objects; b. a behavioral modeler, functionally linked to the viewer system; c. a ranking application operatively linked to the neuropsychological modeling engine; d. a first memory, operably linked to the ranking application, the neuropsychological modeling engine, and the behavioral modeller for storing a plurality of viewer models; e. a second memory, operatively linked to the ranking application, the neuropsychological modeling engine, and the behavioral modeler for storing channel models and content object arrangements in relation to a channel model; wherein the neuropsychological modeling engine is configured to: i) compare meta-data associated with a content object, received from the source of indexed content objects, meta-data associated with a viewer model and at least one viewer channel associated with the viewer, and ii) determining whether the received content object is eligible to be arranged among other content objects associated with the viewer channel in accordance with the viewer's emotional motivation to select the content object.

2. The system according to point 1, wherein the recommendation system further comprises: f. a mathematical model for human emotions, stored in memory and accessible to the neuropsychological modeling engine.

The system of points 1 or 2 wherein the neuropsychological modeling engine is further configured to: iii) generate a fear vector value representing an individual's fear of selecting or purchasing the content object; iv) generate a desire vector value that represents an individual's desire to select or purchase the offered item; v) derive a value Ψ from the desire vector value and the fear vector value, which represents an individual's state of mind; vi) deriving a value m from the desire vector value and the fear vector value, which represents an individual's motivational strength to select the content object; and vii) if the value Ψ representing an individual's state of mind is within an acceptable predetermined range, provide the value m to the ranking application.

The system according to points 1 to 3, wherein the ranking application is configured to determine, using the value m received from the neuropsychological modeling engine, a ranking for the content object in relation to other content objects associated with the channel model.

5. A system consisting of a recommendation system according to one of points 1 to 4 and one or more content objects arranged and / or offered by the recommendation system.

A method for modeling the psychology of a buyer / buyer, comprising: a. Comparing meta-data associated with a content object with meta-data associated with a channel model; b. generating a fear vector value that represents an individual's fear of selecting or purchasing the content object; c. generating a desire vector value that represents an individual's desire to select or purchase the offered item; d. deriving, from the desire vector value and the fear vector value, a value Ψ representing an individual's state of mind; e. deriving, from the desire vector value and the fear vector value, a value m that represents an individual's motivational strength to select or purchase the content object; and f. if the value Ψ representing an individual's state of mind is within an acceptable predetermined range, using the value m to determine a ranking for the content object in relation to other content objects associated with the channel model; scary. storing the channel model and a viewing model associated with the individual in a network-accessible memory.

A system for modeling the psychology of a buying / buying buyer, consisting of: a. A first network-accessible memory for storing at least one channel model; b. a modeling engine, functionally coupled to the network-accessible memory and configured to compare meta-data associated with a content object with meta-data associated with the channel model and to generate: i) a fear vector value that an individual fears (repulsion) proposes to select or purchase the content object; ii) a desire vector value that represents an individual's desire to select or purchase the item offered; iii) a value Ψ representing an individual's state of mind, the value Ψ derived from the desire vector value and the a n g stvecto rwa a rd e; iv) a value m representing an individual's motivational strength to select the content object, the value m derived from the desire vector value and the fear vector value; and c. an arrangement module responsive to the modeling engine to derive an arrangement for the content object in relation to other content objects associated with the channel model, from the value m generated by the modeling engine, if the value Ψ generated by the modeling engine is within an acceptable predetermined range ; and d. a second network-accessible memory for storing at least a portion of the content object and the other content objects.

8. A system consisting of a system according to point 7 and one or more content objects arranged by the system according to point 7.

A method for enabling multi-dimensional surfing, comprising: a. Evaluating a first content object corresponding to behavioral metadata associated with a consumer to determine eligibility for ranking; b. assigning an emotional motivation value to the first content object, if eligible for ranking; and c. arranging a reference to the first content object between a first plurality of references to content objects in order of increasing or decreasing emotional motivation associated with the respective content objects.

10. The method according to point 9, further comprising: d. assigning a chronological ranking value to the first content object between a second plurality of content objects with at least one parameter value in common with the first content object.

The method according to points 9 or 10, further comprising: e. arranging the first content object between a second plurality of content objects with at least one parameter value in common with the first content object in order of increasing or decreasing chronological ranking value.

A method for use with a video display system consisting of a video screen and a plurality of cursor navigation controls to sequentially move a user-selectable sub-area of the video screen surface in one or more directions, the method comprising: a. Receiving a first cursor navigation command; and B. forwarding the first cursor navigation command to start a presentation of a first content object from a first plurality of content objects that were previously arranged according to chronological order or progressively increasing or decreasing emotional motivation.

13. In a video display system consisting of: - a video screen; - a plurality of directional navigation controls to sequentially move a user selectable portion of the video screen in one or more directions over the video screen surface; control logic for receiving command signals associated with one of the navigation controls and for passing the command signal to start a presentation of a first content object from a first plurality of content objects arranged in order of progressive emotional motivation; - wherein selection of a navigation control associated with a first direction starts a presentation of the first content object with at least the same or an increased emotional value than a previously presented content object; and - wherein the selection of a navigation control associated with a second direction, opposite the first direction, starts a presentation of the first content object with at least the same or reduced emotional motivation than a previously presented content object; and a plurality of memory buffers for storing at least a portion of the first plurality of content objects and the first content object.

14. The system according to item 13, further comprising: - control logic for receiving command signals associated with one of the navigation controls and for routing command signals to start a presentation of the first content object from a second plurality of content objects previously arranged in chronological order.

15. In a video display system, consisting of: - a video screen; - a plurality of directional navigation controls for sequentially moving a user selectable portion of the video screen in one or more directions over the video screen surface; control logic for receiving command signals associated with one of the navigation controls and for selecting a first content object from a first plurality of content objects arranged in order of increasing or decreasing emotional motivation and to start a presentation of the first content object from a second plurality of content objects previously arranged in chronological order.

16. In a video display system, consisting of: - a video screen; - a plurality of directional navigation controls for sequentially moving a user selectable portion of the video screen in one or more directions over the video screen surface; - control logic for receiving command signals associated with one of the navigation controls and for forwarding the command signal to start a presentation of the first content object from a first plurality of content objects previously arranged in chronological order.

- wherein selecting a navigation control associated with a first direction starts a presentation of the first content object with a prior chronological value than a previously presented content object; and wherein selecting a navigation control associated with a second direction, opposite to the first direction, starts a presentation of the first content object with a later chronological value than a previously presented content object; and a plurality of memory buffers to store at least a portion of the first plurality of content objects and the first content object.

A system according to any of points 13 to 16 wherein at least one of the navigation controls is selected from navigation controls for up, down, left or right.

A system according to any of points 13 to 17 wherein at least a portion of the first plurality of content objects is displayed at the same time with the first content object.

A system according to any of points 13 to 18 wherein at least a portion of the second plurality of content objects is displayed at the same time with the first content object.

A system according to any of points 13 to 19 wherein part of the first or second plurality of content objects are displayed with graphical indicia indicating which navigation controls are thereby available.

A system consisting of a system according to one of points 13 to 20 and one or more content objects arranged and / or selected with a system according to one of points 13 to 20.

A system for displaying and navigating multiple data streams, comprising: a video screen that defines a video screen surface; - a control interface operatively coupled to the video screen and configured to provide a plurality of directional navigation controls to sequentially move a user selectable sub-area within the video screen surface in one or more directions; and a graphics engine for receiving command signals associated with one of the navigation controls to start a presentation of a primary content object from a first plurality of content objects arranged according to predetermined criteria.

23. The system of item 22 wherein the first plurality of content objects are arranged in a predetermined order of increasing or decreasing emotional motivation of a viewer to select the content objects.

The system of point 23 wherein selecting a navigation control associated with a first direction starts a presentation of the primary content object with at least the same or increased emotional motivation than a previously presented content object.

25. The system according to item 24 wherein selecting a navigation control associated with a second direction, opposite to the first direction, starts a presentation of the primary content object with at least the same or reduced emotional motivation than a previously presented content object.

26. The system according to item 22 wherein the first plurality of content objects were previously arranged in chronological order.

27. The system of item 26 wherein selecting a navigation control associated with a first direction starts a presentation of the primary content object with a prior chronological value than a previously presented content object.

28. The system according to point 27 wherein selecting a navigation control associated with a second direction, opposite to the first direction, starts a presentation of the primary content object with a later chronological value associated with it than a previously presented content object.

The system of any of points 22 to 28, wherein the graphics engine is configured to display at least a portion of the first plurality of content object data streams at the same time as displaying the primary content object data stream.

30. The system of item 29 wherein the portion of the first plurality of content object data streams is displayed with graphical indicia indicating which directional navigation controls are selectable thereby.

The system according to any of points 29 to 30 wherein the portion of the first plurality of content object data streams is displayed with graphical indicia indicating the price associated with its selection.

The system according to any of points 29 to 31 wherein the primary data stream data content is displayed with graphical indicia indicating an authorization status associated with its selection.

33. The system according to any of points 19 to 32 wherein the primary data stream with content objects is displayed with descriptive information about it.

34. The system according to item 22 wherein the first plurality of content objects are arranged in a predetermined order according to the price associated with their selection.

35. The system of item 34 wherein selecting a navigation control associated with a first direction starts a presentation of the primary content object at no cost associated with its selection.

36. The system of item 35 wherein selecting a navigation control associated with a second direction, opposed to the first direction, starts a presentation of the primary content object with a price associated with its selection.

The system of any one of points 22 to 36 wherein a control interface is further configured to provide a plurality of controls to provide explicit feedback in the form of negative or positive emotion toward the primary content object or metadata that associated with this.

38. The system according to any of points 22 to 37, wherein a control interface further comprises a plurality of color-coded controls that can be used to socially share the link to the primary content object with the appropriate social network or to provide a gift to the author (s) of the primary content object or its recommender.

39. The system according to any of points 22 to 38, wherein the control interface further comprises accelerometers to detect horizontal, vertical, and other motion patterns for use as navigation and selection commands.

40. The system according to any of points 22 to 39, wherein the graphics engine is further configured to display on the video screen images of third parties that have recommended content, the images presented in a row relationship with a recommender of the primary content object.

41. The system according to any of points 22 to 40, wherein the system further comprises one or more virtual channels in which content objects come from single or multiple sources, external to the recommendation system, and can be arranged in any of the following categories: recommended content, guided content, third-party content, personal library content, user-generated content and images, mail, posted content and offline viewing of any of previous or regular channels.

42. The system of any one of points 22 to 41 wherein the control interface is further configured to navigate between content objects arranged in dimensions and wherein the dimensions are logically nestled at multiple levels.

43. The system according to point 42 wherein the control interface is further configured to navigate between either a chronological arrangement of chronologically ordered content objects, or a vertical anxiety / desire dimension.

44. The system according to any of points 22 to 43, wherein the control interface is further configured to provide a command, a channel pointer or a display icon to access, and immediately present, as a primary content object, instructional materials relating to various functions and procedures associated with the system.

45. A system consisting of a system according to one of points 22 to 44 and a content object presented and / or selected with the aid of a system according to one of points 22 to 44.

46. A method for distributed delayed content streaming comprising: a. Providing a network-accessible memory for storing content that represents a first program; b. receiving in the network-accessible memory portions of the first program from a plurality of viewers that access the first program from another source; c. editing the portions received from the plurality of viewers in the first program; and d. upon receipt of a request from one of the plurality of viewers, forwarding the first program to the requesting viewer.

wherein the portions of the first program are received asynchronously from the plurality of viewers; wherein the first program is accessible to the plurality of viewers from the other source during a first period and wherein the first program is forwarded to the requesting viewer during a second period not identical to the first period.

47. A system for distributed delayed content streaming comprising: a. A network-accessible memory for storing content representing the first program; b. a network interface for receiving in the network accessible memory at least portions of the first program from a plurality of viewers having access to the first program from another source; c. a combination engine for mounting the portions received from the plurality of viewers in the first program; and d. a streaming interface for sending the first program to one of the plurality of on-demand viewers.

48. A system consisting of a system according to point 47 and one or more programs suitable for a system according to point 47.

49. A method for distributed content upload comprising: a. Determining which of a plurality of content programs are accessible from a first source for downloading to a viewer system; b. requesting to download at least a portion of accessible programs from the first source to the viewer system at a first time; c. uploading at least a portion of the accessible program received by the viewer system to a second remote source together with permission indicia to identify the viewer system; and d. requesting to download the accessible program from the second source to the viewer system at a second time different from the first time.

50. A system for distributed uploading of content consisting of: a. A viewer system functionally linked via a network to a first source of content programs; b. program logic to determine which of a plurality of content programs are accessible from the first source and to request downloading at least a portion of accessible programs from the first source to the viewer system at a first time point; and c. program logic for uploading at least a portion of the accessible program received by the viewer system to a second remote source together with the consent indicia for identifying the viewer system; and d. program logic for requesting downloading the accessible program from the second source to the viewer system at a second time different from the first time.

51. The system of point 50 further comprising: e. program logic for receiving streamed download of a part of the accessible program from the second source, wherein the streamed download part of the accessible program received from the second remote source is greater than the uploaded part of the accessible program transferred to the second source remotely from the viewer system.

52. A system consisting of a system according to one of points 50 or 51 and one or more content programs suitable for a system according to one of points 50 or 51.

53. A method for distributed delayed streaming of content, comprising: a. Providing a network-accessible memory for storing content that represents a first program received from a source; b. receiving, in the network-accessible memory, permission indicia identifying a plurality of viewers having access to the first program from the source; and c. upon receiving a request from one of the plurality of viewers, verifying the permission indicia to determine whether requesting viewer has authorized access to the program; and d. forwarding the first program to the requesting viewer after verification of the permission, wherein the first program is accessible to the plurality of viewers from the source during a first period and wherein the first program is forwarded to the requesting viewer during a second period not identical to the first period.

54. A system for distributed delayed streaming of content, consisting of: a. A network-accessible memory for storing content that represents a first program received from a source; b. a network interface for receiving in the network-accessible memory of permission indicia for identifying a plurality of viewers having access to the first program from the source; c. a check engine for determining, upon receipt of a request from one of the plurality of viewers, whether the requesting viewer has authorized access to the first program; and d. a streaming interface for sending the first program to the requesting viewer after verification of the admission.

55. A system consisting of a system according to point 54 and one or more programs suitable for a system according to point 54.

56. A system content selection and viewing system, comprising: a. A first user interface operably linked to the composition of selectable and viewable content objects for presenting substantial visual, non-textual information; b. a second user interface operably linked to the data associated with the content objects for presenting substantial textual information; c. a third user interface functionally linked to the composition of selectable and viewable content objects and the meta-data associated with the content objects for presenting visual content or textual information; and d. a network-accessible memory for storing at least a portion of the meta-data associated with the content objects.

57. A system consisting of a system according to point 56 and one or more content objects suitable for a system according to point 56.

58. A method for selecting and viewing program content, comprising: a. Providing a first user interface operably linked to the composition of selectable and viewable content objects for presenting substantial visual, non-textual information; b. providing a second user interface operably linked to meta-data associated with the content objects for presenting substantial textual information, and c. providing a third user interface operably linked to the composition of selectable and viewable content objects and the meta-data associated with the content objects for presenting visual content and textual information; and d. storing in a network-accessible memory of at least a portion of the meta-data associated with the content objects.

Claims (3)

A method for distributed delayed streaming of content comprising: a. Providing a network-accessible memory for storing content representing a first program; b. receiving in the network-accessible memory portions of the first program from a plurality of viewers that access the first program from another source; c. editing the portions received from the plurality of viewers in the first program; and d. upon receipt of a request from one of the plurality of viewers, forwarding the first program to the requesting viewer. wherein the portions of the first program are received asynchronously from the plurality of viewers; wherein the first program is accessible to the plurality of viewers from the other source during a first period and wherein the first program is forwarded to the requesting viewer during a second period not identical to the first period. 2. A system for distributed delayed streaming of content consisting of: e. a network-accessible memory for storing content representing the first program; f. a network interface for receiving in the network accessible memory at least portions of the first program from a plurality of viewers having access to the first program from another source; g. a combination engine for mounting the portions received from the plurality of viewers in the first program; and H. a streaming interface for sending the first program to one of the plurality of on-demand viewers. A system consisting of a system according to claim 2 and one or more programs suitable for a system according to claim 2.