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CN111460283A - Information processing method, information processing device, electronic equipment and computer readable storage medium - Google Patents

Information processing method, information processing device, electronic equipment and computer readable storage medium Download PDF

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Publication number
CN111460283A
CN111460283A CN202010152708.4A CN202010152708A CN111460283A CN 111460283 A CN111460283 A CN 111460283A CN 202010152708 A CN202010152708 A CN 202010152708A CN 111460283 A CN111460283 A CN 111460283A
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data
presentation data
candidate
target
candidate presentation
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王思远
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Lazas Network Technology Shanghai Co Ltd
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Lazas Network Technology Shanghai Co Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/953Querying, e.g. by the use of web search engines
    • G06F16/9535Search customisation based on user profiles and personalisation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/958Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking

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  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
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  • General Physics & Mathematics (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The embodiment of the invention discloses an information processing method, an information processing device, electronic equipment and a computer readable storage medium, wherein historical information of a target resource is obtained through an obtained identifier of the target resource, a plurality of candidate display data are determined, the candidate display data are respectively used as simulation display data of a target information object, simulation of a historical processing period is carried out according to the historical information to determine simulation exposure data of the candidate display data, and recommended display data of the target information object are determined according to the simulation exposure data, so that the cost performance can be improved while exposure parameters, click parameters and conversion parameters of the target information object are improved.

Description

Information processing method, information processing device, electronic equipment and computer readable storage medium
Technical Field
The present invention relates to the field of internet technologies, and in particular, to an information processing method and apparatus, an electronic device, and a computer-readable storage medium.
Background
In the network exhibition platform, the exhibition party usually needs to compete to make the exhibition content of the own party exhibited in the network exhibition platform. At present, in order to improve the exposure rate, click rate and conversion rate of the display content, the display party generally needs to add the presentation data, which makes the display party blind when providing the presentation data.
Disclosure of Invention
In view of this, embodiments of the present invention provide an information processing method, an information processing apparatus, an electronic device, and a computer-readable storage medium, so as to determine recommended presentation data of a target information object according to history information of a target resource, thereby improving a performance-to-price ratio while improving an exposure parameter, a click parameter, and a conversion parameter of the target information object.
In a first aspect, an embodiment of the present invention provides an information processing method, where the method includes:
receiving a data instruction from a client;
analyzing the data instruction through at least one processor to obtain the identification of the target resource;
acquiring, by at least one processor, history information of the target resource according to the identifier of the target resource, where the history information includes presentation data of a plurality of information objects of the target resource in a history processing period, and the presentation data is used to represent willingness of each information object to acquire the target resource in a corresponding history processing period;
determining, by at least one processor, a plurality of candidate presentation data;
respectively taking the candidate presentation data as simulation presentation data of a target information object, and performing simulation of a historical processing period through at least one processor according to the historical information to determine simulation exposure data of the candidate presentation data;
determining, by at least one processor, recommended presentation data for the target information object based on the respective simulated exposure data.
Optionally, the determining, by using the simulation display data of the target information object and using each candidate display data as the simulation display data of the target information object, the simulation of the history processing cycle according to the history information by the at least one processor, includes:
in response to the candidate presentation data being determined to be target presentation data of a corresponding historical processing cycle, acquiring simulated exposure parameters of the candidate presentation data in the corresponding historical processing cycle, the target presentation data being a maximum value of a plurality of presentation data in the corresponding historical processing cycle;
and determining simulated exposure data of the candidate presentation data according to the simulated exposure parameters of the candidate presentation data in each historical processing period.
Optionally, determining simulated exposure data of the candidate presentation data according to the simulated exposure parameters of the candidate presentation data in each historical processing cycle includes:
and calculating the weighted sum of the simulated exposure parameters of the candidate presentation data in each historical processing period to obtain the simulated exposure data of the candidate presentation data.
Optionally, determining, by the at least one processor, recommended presentation data of the target information object according to the respective simulated exposure data includes:
sorting the simulation exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation exposure data adjacent to each other;
determining the recommended presentation data from the plurality of candidate presentation data based on the difference.
Optionally, determining, by the at least one processor, recommended presentation data of the target information object according to the respective simulated exposure data includes:
determining simulated click data corresponding to each candidate presentation data according to the simulated exposure data and the click parameters of the target information object;
sorting the simulation click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation click data adjacent to each other;
determining the recommended presentation data from the plurality of candidate presentation data based on the difference.
Optionally, determining, by the at least one processor, recommended presentation data of the target information object according to the respective simulated exposure data includes:
determining first pre-recommendation data from candidate presentation data according to the simulation exposure data;
determining second pre-recommendation data according to the historical information and the click parameters of the target information object;
and determining recommended presentation data of the target information object according to the first pre-recommended data and the second pre-recommended data.
Optionally, determining first pre-recommendation data from candidate presentation data according to the simulation exposure data includes:
sorting the simulation exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation exposure data adjacent to each other;
determining the first pre-recommendation data from the plurality of candidate presentation data according to the difference.
Optionally, determining first pre-recommendation data from candidate presentation data according to the simulation exposure data includes:
determining simulated click data corresponding to each candidate presentation data according to the simulated exposure data and the click parameters of the target information object;
sorting the simulation click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation click data adjacent to each other;
determining the first pre-recommendation data from the plurality of candidate presentation data according to the difference.
Optionally, the history information further includes target presentation data in each history processing cycle, and click parameters of information objects corresponding to each target presentation data;
determining second pre-recommendation data according to the historical information and the click parameters of the target information object comprises:
calculating the product of the target presentation data in each history processing period and the click parameter of the corresponding information object to obtain a plurality of corresponding first parameters;
calculating the ratio of each first parameter to the click parameter of the target information object respectively to obtain a plurality of corresponding pre-recommendation parameters;
calculating an average value of the plurality of pre-recommendation parameters to obtain the second pre-recommendation data.
Optionally, determining the recommended presentation data of the target information object according to the first pre-recommended data and the second pre-recommended data includes:
and calculating the weighted sum of the first pre-recommended data and the second pre-recommended data according to a preset weight so as to obtain the recommended presentation data of the target information object.
In a second aspect, an embodiment of the present invention provides an information processing apparatus, including:
an instruction receiving unit configured to receive a data instruction from a client;
the identification acquisition unit is configured to analyze the data instruction through at least one processor to acquire the identification of the target resource;
a history information obtaining unit configured to obtain, by at least one processor, history information of the target resource according to the identifier of the target resource, where the history information includes presentation data of a plurality of information objects of the target resource in a history processing period, and the presentation data is used to represent willingness of each information object to obtain the target resource in a corresponding history processing period;
a candidate presentation data determination unit configured to determine, by at least one processor, a plurality of candidate presentation data;
the simulation exposure data determining unit is configured to respectively use each candidate presentation data as simulation presentation data of a target information object, and perform simulation of a history processing period according to the history information through at least one processor so as to determine simulation exposure data of each candidate presentation data;
a recommended presentation data determination unit configured to determine, by at least one processor, recommended presentation data for the target information object from the respective simulated exposure data.
Optionally, the simulated exposure data determining unit includes:
a simulated exposure parameter determination subunit configured to, in response to the candidate presentation data being determined as target presentation data of a corresponding historical processing cycle, acquire a simulated exposure parameter of the candidate presentation data in the corresponding historical processing cycle, the target presentation data being a maximum value among a plurality of presentation data in the corresponding historical processing cycle;
and the simulated exposure data determining subunit is configured to determine simulated exposure data of the candidate presentation data according to the simulated exposure parameters of the candidate presentation data in each historical processing period.
Optionally, the simulation exposure data determining subunit includes:
and the simulated exposure data determination module is configured to calculate the weighted sum of the simulated exposure parameters of the candidate presentation data in each historical processing period, and acquire the simulated exposure data of the candidate presentation data.
Optionally, the recommended presentation data determining unit includes:
the first sequencing subunit is configured to sequence the simulation exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
a first difference calculation subunit configured to calculate differences of two adjacent pairs of the simulated exposure data, respectively;
a first recommended presentation data determining subunit configured to determine the recommended presentation data from the plurality of candidate presentation data according to the difference.
Optionally, the recommended presentation data determining unit includes:
the simulated click data determining subunit is configured to determine simulated click data corresponding to each candidate presentation data according to each simulated exposure data and the click parameter of the target information object;
the second sorting subunit is configured to sort the simulation click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
the second difference calculation subunit is configured to calculate differences of the two adjacent simulated click data respectively;
a second recommended presentation data determining subunit configured to determine the recommended presentation data from the plurality of candidate presentation data according to the difference.
Optionally, the recommended presentation data determining unit includes:
a first pre-recommendation data determination subunit configured to determine first pre-recommendation data from the candidate presentation data according to the respective simulated exposure data;
the second pre-recommendation data determining subunit is configured to determine second pre-recommendation data according to the historical information and the click parameters of the target information object;
and the third recommended presentation data determining subunit determines the recommended presentation data of the target information object according to the first pre-recommended data and the second pre-recommended data.
Optionally, the first pre-recommendation data determining subunit includes:
the first sequencing module is configured to sequence the simulation exposure data corresponding to each candidate presentation data according to the numerical value of the candidate presentation data;
the first difference calculation module is configured to calculate the difference of the two adjacent simulation exposure data respectively;
a first pre-recommendation data determination module configured to determine the first pre-recommendation data from the plurality of candidate presentation data according to the difference.
Optionally, the first pre-recommendation data determining subunit includes:
the simulation click data determining module is configured to determine simulation click data corresponding to each candidate presentation data according to each simulation exposure data and the click parameter of the target information object;
the second sorting module is configured to sort the simulation click data corresponding to each candidate presentation data according to the numerical value of the candidate presentation data;
the second difference calculation module is configured to calculate the difference between every two adjacent simulation click data respectively;
a second pre-recommendation data determination module configured to determine the first pre-recommendation data from the plurality of candidate presentation data according to the difference.
Optionally, the history information further includes target presentation data in each history processing cycle, and click parameters of information objects corresponding to each target presentation data;
the second pre-recommendation data determination subunit includes:
the first parameter calculation module is configured to calculate the product of the target presentation data in each history processing period and the click parameter of the corresponding information object respectively so as to obtain a plurality of corresponding first parameters;
the pre-recommendation parameter calculation module is configured to calculate a ratio of each first parameter to a click parameter of the target information object to obtain a plurality of corresponding pre-recommendation parameters;
a second pre-recommendation data obtaining module configured to calculate an average value of the plurality of pre-recommendation parameters to obtain the second pre-recommendation data.
Optionally, the third recommendation presentation data determining subunit includes:
and the recommendation presentation data module is configured to calculate a weighted sum of the first pre-recommendation data and the second pre-recommendation data according to a preset weight so as to obtain recommendation presentation data of the target information object.
In a third aspect, an embodiment of the present invention provides an electronic device, including a memory and a processor, where the memory is used to store one or more computer program instructions, where the one or more computer program instructions are executed by the processor to implement the method described above.
In a fourth aspect, embodiments of the present invention provide a computer readable storage medium having stored thereon computer program instructions which, when executed by a processor, implement a method as described above.
According to the embodiment of the invention, the historical information of the target resource is obtained through the obtained identification of the target resource, the candidate display data are determined, the candidate display data are respectively used as the simulation display data of the target information object, the simulation of the historical processing period is carried out according to the historical information so as to determine the simulation exposure data of the candidate display data, and the recommended display data of the target information object is determined according to the simulation exposure data, so that the cost performance can be improved while the exposure parameter, the click parameter and the conversion parameter of the target information object are improved.
Drawings
The above and other objects, features and advantages of the present invention will become more apparent from the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a method of information processing according to an embodiment of the present invention;
FIG. 2 is a schematic coordinate diagram of candidate presentation data and simulated click data according to an embodiment of the present invention;
FIG. 3 is a flow chart of another information processing method of an embodiment of the present invention;
FIG. 4 is a flow chart of yet another information processing method of an embodiment of the present invention;
FIG. 5 is a schematic diagram of an information processing apparatus of an embodiment of the present invention;
fig. 6 is a schematic diagram of an electronic device of an embodiment of the invention.
Detailed Description
The present invention will be described below based on examples, but the present invention is not limited to only these examples. In the following detailed description of the present invention, certain specific details are set forth. It will be apparent to one skilled in the art that the present invention may be practiced without these specific details. Well-known methods, procedures, components and circuits have not been described in detail so as not to obscure the present invention.
Further, those of ordinary skill in the art will appreciate that the drawings provided herein are for illustrative purposes and are not necessarily drawn to scale.
Unless the context clearly requires otherwise, throughout the description, the words "comprise", "comprising", and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is, what is meant is "including, but not limited to".
In the description of the present invention, it is to be understood that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. In addition, in the description of the present invention, "a plurality" means two or more unless otherwise specified.
Fig. 1 is a flowchart of an information processing method according to an embodiment of the present invention. As shown in fig. 1, the information processing method according to the embodiment of the present invention includes the steps of:
step S110, receiving a data command from the client. Optionally, when the client needs to request to obtain the current presentation data, the data instruction is sent.
Step S120, analyzing the data command by at least one processor to obtain an identifier of the target resource.
Step S130, obtaining the historical information of the target resource according to the identification of the target resource through at least one processor. The historical information of the target resource comprises the presentation data of a plurality of information objects of the target resource in a historical processing period, and the presentation data is used for representing the willingness of each information object to acquire the target resource in the corresponding processing period. Optionally, in a processing cycle, the larger the presentation data of the information object, the stronger the willingness of the information object to acquire the target resource in the processing cycle. In an alternative implementation manner, the present embodiment may obtain historical information of the target resource in the same time interval. In some areas, such as advertising spots on take-away platforms, since at noon 11: 00-13: 00. in the afternoon 17: 00-19: 00 is the dining time, therefore, the information object (the takeaway merchant, etc.) acquires the advertisement space of the time intervals, namely, the advertisement space is exposed in the time intervals, and the click rate and the conversion rate are higher.
Taking the target resource as an advertisement slot as an example, the information object may be a presenter or presentation content of the presenter. Multiple presenters may obtain the ad slot by competition to present the own-party presentation during the same time interval (e.g., 11: 00-13: 00 noon of each day during a month). The historical information for the target resource includes presentation data presented by the presenters during the historical processing period. Wherein the presentation data of the information object may be a cost parameter (e.g., competitive price, etc.) paid by the information object. It should be understood that, in the present embodiment, the target resource is taken as an advertisement slot, but the present embodiment does not limit this, and any resource that needs to compete by multiple parties may be taken as the target resource of the present embodiment, for example, a display position of news, goods, or merchant information on a page.
In step S140, a plurality of candidate presentation data is determined by at least one processor. In an alternative implementation, the candidate presentation data may be determined according to a plurality of target presentation data corresponding to the target resource in a plurality of historical processing cycles. The target presentation data is the maximum value of the plurality of presentation data in the corresponding history processing cycle, that is, the presentation data of the information object bound to the target resource. For example, in the history processing cycle, the range of the target presentation data corresponding to the target resource is 10 to 80, the presentation data in the range may be regarded as candidate presentation data in units of 1, that is, 1, 2, 3, …, 79, and 80, or the presentation data in the range may be regarded as candidate presentation data in units of 10, that is, 10, 20, …, 70, and 80, and this embodiment is not limited thereto. In another alternative implementation, the at least one candidate presentation data may also be determined based on a historical presentation data range of the target information object.
Step S150, respectively taking each candidate presentation data as simulation presentation data of the target information object, and performing, by at least one processor, simulation of a history processing cycle according to history information of the target resource to determine simulation exposure data of each candidate presentation data.
In an alternative implementation, step S150 includes:
in response to the candidate presentation data being determined to be target presentation data for a corresponding historical processing cycle, simulated exposure parameters of the candidate presentation data in the corresponding historical processing cycle are obtained. Wherein the target presentation data is a maximum value among the plurality of presentation data in the corresponding history processing cycle. Optionally, in the simulation process of the history processing cycle, if the candidate presentation data is determined to be the target presentation data, the simulated exposure parameter is an actual exposure parameter of the information object bound to the target resource in the history processing cycle. If the candidate presentation data is not determined to be the target presentation data, the simulated exposure parameter is 0.
And determining simulated exposure data of the candidate presentation data according to the simulated exposure parameters of the candidate presentation data in each historical processing period.
In an alternative implementation manner, the sum of simulated exposure parameters of the candidate presentation data in each historical processing period is calculated, and simulated exposure data of the candidate presentation data is obtained. In another alternative implementation, a weighted sum of simulated exposure parameters of the candidate presentation data in each historical processing period is calculated to obtain simulated exposure data of the candidate presentation data. Optionally, the weight of each simulated exposure parameter may be determined according to the time of the corresponding historical processing cycle, for example, the weight of the simulated exposure parameter corresponding to the historical processing cycle that is shorter than the current time is larger, so that the prediction accuracy of the current presentation data may be further improved. It should be understood that the present embodiment is not limited to the method for acquiring the simulated exposure data, and other methods for acquiring the simulated exposure data, such as calculating the average value of each simulated exposure parameter, may be applied to the present embodiment.
In an alternative implementation manner, when a target information object participates in each history processing cycle of a target resource, the actual display data of the target information object in the history processing cycle is replaced by candidate display data, and the display data of other information objects is not changed so as to simulate each history processing cycle of the target resource, thereby acquiring the corresponding simulated exposure data when the target information object displays the candidate display data.
For example, it is assumed that the history information of the target resource M in N (N >1, which is exemplified by N ═ 5 in the present embodiment) history processing cycles is as shown in table (1).
Watch (1)
Figure BDA0002403003080000101
As shown in Table (1), in the 1 st history processing cycle, the information object A4 is bound with the target resource M, and the actual exposure parameter is x 1. In the 2 nd history processing cycle, the information object A2 is bound with the target resource M, and the actual exposure parameter is x 2. In the 3 rd history processing cycle, the information object A3 is bound with the target resource M, and the actual exposure parameter is x 3. In the 4 th history processing cycle, the target information object is bound with the target resource M, and the actual exposure parameter is x 4. In the 5 th history processing cycle, the information object A1 is bound with the target resource M, and the actual exposure parameter is x 5.
The presentation data of the target information object in the N history processing cycles is replaced with a candidate presentation data 10, and the procedure of the simulation information processing is as shown in table (2).
Watch (2)
Figure BDA0002403003080000102
Figure BDA0002403003080000111
As shown in table (2), in the simulation process of the 1 st history processing cycle, if the presentation data of the target information object is the candidate presentation data 10, the target information object can be bound with the target resource, and in the other history processing cycles, if the presentation data of the target information object is the candidate presentation data 10, the target information object cannot be bound with the target resource. Thus, when the candidate presentation data is 10, the simulated exposure parameters of the target information object include x1', and the simulated exposure data Y1 ═ q1 × 1' corresponding to the candidate presentation data 10 are given by taking the weights of the simulated exposure parameters corresponding to the respective history processing cycles as q1-q5 as examples.
The presentation data of the target information object in the N history processing cycles is replaced with a candidate presentation data 15, and the procedure of the simulation information processing is as shown in table (3).
Watch (3)
Figure BDA0002403003080000112
As shown in table (2), in the simulation process of the 1 st to 4 th history processing cycles, if the presentation data of the target information object is the candidate presentation data 15, the target information object can be bound with the target resource, and in the 5 th history processing cycle, if the presentation data of the target information object is the candidate presentation data 15, the target information object cannot be bound with the target resource. Thus, when the candidate presentation data is 15, the simulated exposure parameters of the target information object include x1', x2', x3 'and x4', and the simulated exposure data Y2 ═ q1 × 1'+ q2 × 2' + q3 × 3'+ q4 × 4' corresponding to the candidate presentation data 15 is exemplified by the weights q1-q5 of the simulated exposure parameters corresponding to the respective history processing cycles.
In an optional implementation manner, when the target information object does not participate in each history processing period of the target resource, behavior information of the target information object presentation candidate presentation data is added in the history processing period, and presentation data of other information objects is not changed, so that corresponding simulated exposure data is acquired when the target information object presents the candidate presentation data in the history processing period of the target resource. In another optional implementation manner, the target information object is a new information object, and does not participate in any competitive behavior, that is, the history information of the target resource does not have the presentation data of the target information object. At this time, a reference information object may be screened from the historical information, the similarity between the reference information object and the target information object is greater than a similarity threshold, the historical processing data of the reference information object (i.e., the behavior information of each historical processing cycle in which the reference information object participates) is assigned to the target information object, and the simulated exposure data when the target information object presents each candidate presentation data is obtained according to the similar manner described above. Optionally, the similarity may be determined according to the attribute information, and the attribute information of the information object may include a category, a geographical location, and the like of the information object. For example, the category of the information object includes a takeout merchant and a takeout merchant type (chuanxiong dish, cantonese dish, etc.) of the takeout platform, and the geographic location is the location of the takeout merchant.
In step S160, recommended presentation data for the target information object is determined by the at least one processor from the respective simulated exposure data.
In an alternative implementation, step S160 includes:
and sorting the simulation exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data. For example, the candidate presentation data includes 10, 12, 14, 16, 18, and 20, and the simulated exposure data corresponding to the candidate presentation data is Y10, Y12, Y14, Y16, Y18, and Y20, and the data sequence formed by sorting the simulated exposure data is { Y10, Y12, Y14, Y16, Y18, and Y20}, or { Y20, Y18, Y16, Y14, Y12, and Y10 }.
And respectively calculating the difference value of the simulation exposure data adjacent to each other. Taking the data sequence { Y10, Y12, Y14, Y16, Y18, Y20} as an example, the differences of the simulation exposure data adjacent to each other are Y12-Y10, Y14-Y12, Y16-Y14, Y18-Y16, and Y20-Y18, respectively.
Determining the recommended presentation data from the plurality of candidate presentation data based on the difference. Assume that, in the above example, Y12-Y10-2, Y14-Y12-3, Y16-Y14-10, Y18-Y16-1, and Y20-Y18-2. Thus, when the presentation candidate data increases from 14 to 16, a large increase in the simulated exposure data occurs, and when the presentation candidate data increases from 16 to 18, the simulated exposure data changes less, and therefore, the presentation candidate data 16 may be determined as the recommended presentation data.
In the processing period of the target resource, the higher the presentation data is, the higher the probability of acquiring the target resource is, but when the presentation data is increased to a certain value, the target resource can be acquired in each processing period or most processing periods, that is, even if the presentation data is increased again, the exposure rate of the target information object is basically not changed. Therefore, in the embodiment, recommended presentation data is determined from the candidate presentation data by adopting the difference value of every two adjacent exposure data, so that the presentation data can be further prevented from being improved blindly, and the cost performance can be improved while the exposure parameters, the click parameters and the conversion parameters of the target information object are improved.
In another alternative implementation, step S160 includes:
and determining simulated click data corresponding to the candidate presentation data according to the simulated exposure data and the click parameters of the target information object. In an optional implementation manner, the product of each simulated exposure data and the click parameter of the target information object is calculated to obtain simulated click data corresponding to each candidate presentation data. Alternatively, the click parameter may be determined by the historical number of clicks of the target information object.
And sorting the simulation click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data. Taking the data in tables (2) and (3) as an example, assuming that the click parameter of the target information object is D, the simulated click data D10 corresponding to the candidate presentation data 10 is Y1D, and the simulated click data D15 corresponding to the candidate presentation data 15 is Y2D.
And respectively calculating the difference value of the simulation click data adjacent to each other, and determining the recommended presentation data from the candidate presentation data according to the difference value.
Fig. 2 is a schematic diagram of coordinates of candidate presentation data and simulated click data according to an embodiment of the present invention, where, as shown in fig. 2, the historical processing cycle in the above table (1) is described, and the candidate presentation data is 10-18, for example, the historical processing cycle is simulated, where the abscissa is the candidate presentation data and the ordinate is the simulated click data corresponding to the candidate presentation data presented by the target information object, alternatively, the difference between two adjacent simulated click data is calculated, respectively, and the recommended presentation data is determined from the candidate presentation data according to the difference, where the slope of a linear fit function formed by coordinate points of two adjacent candidate presentation data objects is calculated, and the recommended presentation data is determined from the candidate presentation data corresponding to the linear fit function with the maximum slope, as shown in fig. 2, in the linear fit function formed by coordinate points corresponding to two adjacent candidate presentation data objects, the slope of the linear fit function L1 is maximum, and thus, the candidate presentation data 15 is determined as the recommended presentation data, thereby effectively avoiding blind presentation data, and improving the performance-price ratio and improving the target parameters and the conversion parameters of the target information object.
According to the embodiment of the invention, the historical information of the target resource is obtained through the obtained identification of the target resource, the candidate display data are determined, the candidate display data are respectively used as the simulation display data of the target information object, the simulation of the historical processing period is carried out according to the historical information so as to determine the simulation exposure data of the candidate display data, and the recommended display data of the target information object is determined according to the simulation exposure data, so that the cost performance can be improved while the exposure parameter, the click parameter and the conversion parameter of the target information object are improved.
In another alternative implementation, step S160 includes:
step S161, determining first pre-recommended data from the candidate display data according to each simulated exposure data, in an optional implementation, sorting the simulated exposure data corresponding to each candidate display data according to the numerical values of the plurality of candidate display data, calculating the difference value between two adjacent simulated exposure data, and determining the first pre-recommended data from the plurality of candidate display data according to the difference value, in another optional implementation, determining the simulated click data corresponding to each candidate display data according to the click parameter of each simulated exposure data and the target information object, sorting the simulated click data corresponding to each candidate display data according to the numerical values of the plurality of candidate display data, calculating the difference value between two adjacent simulated click data, and determining the first pre-recommended data from the plurality of candidate display data according to the difference value, a specific implementation method is similar to the method for obtaining the recommended data in the above embodiment, as shown in fig. 2, in a linear fitting function L formed by coordinate points corresponding to two adjacent candidate display data, and determining the first pre-recommended data as the first pre-recommended data.
And step S162, determining second pre-recommendation data according to the historical information of the target resource and the click parameter of the target information object. Optionally, the history information of the target resource further includes target presentation data in each history processing cycle, and a click parameter of an information object corresponding to each target presentation data.
In an alternative implementation, step S162 includes:
and calculating the product of the target display data in each history processing period and the click parameter of the corresponding information object to obtain a plurality of corresponding first parameters. Taking the historical processing cycles in table (1) as an example, assuming that the click parameters of the information objects a1-a5 are d1-d5, respectively, and the click parameter of the target information object is d, the first parameters corresponding to the processing cycles are 9 × d4, 11 × d2, 14 × d3, 15 × d, and 16 × d1, respectively.
And calculating the ratio of each first parameter to the click parameter of the target information object to obtain a plurality of corresponding pre-recommendation parameters. Taking the historical processing cycles in table (1) as an example, the pre-recommended parameters are 9 × d4/d, 11 × d2/d, 14 × d3/d, 15 × d/d, and 16 × d1/d, respectively.
Calculating an average value of the plurality of pre-recommendation parameters to obtain the second pre-recommendation data. Taking each history processing cycle in table (1) as an example, the second pre-recommendation data is:
Figure BDA0002403003080000151
it should be understood that other methods for calculating the second pre-recommendation data can be applied to the embodiments of the present invention, for example, first calculating the ratio between the information object corresponding to each target presentation data and the target information object, and then calculating the product of each ratio and the corresponding target presentation data.
In step S163, recommendation presentation data of the target information object is determined according to the first pre-recommendation data and the second pre-recommendation data. In an optional implementation manner, a weighted sum of the first pre-recommended data and the second pre-recommended data is calculated according to a preset weight, so as to obtain recommended presentation data of the target information object. As shown in fig. 2, the first pre-recommended data Bi1 is 15, and assuming that the weights of the first pre-recommended data Bi1 and the second pre-recommended data Bi2 are w1 and w2, respectively, the currently presented data Bi of the target information object is w1 Bi1+ w2 Bi 2.
According to the embodiment of the invention, the historical information of the target resource is obtained through the obtained identification of the target resource, the first pre-recommendation data of the target information object is determined from the candidate display data according to the historical information of the target resource, the second pre-recommendation data of the target information object is determined according to the historical information of the target resource and the click parameter of the target information object, and the current display data of the target information object is determined according to the first pre-recommendation data and the second pre-recommendation data, so that the cost performance can be further improved while the exposure parameter, the click parameter and the conversion parameter of the target information object are improved.
Fig. 3 is a flowchart of another information processing method according to an embodiment of the present invention. As shown in fig. 3, the information processing method according to the embodiment of the present invention includes the steps of:
step S310, receiving a data command from the client. Optionally, when the client needs to request to obtain the current presentation data, the data instruction is sent.
Step S320, analyzing the data command by at least one processor to obtain the identifier of the target resource.
Step S330, obtaining the history information of the target resource according to the identification of the target resource through at least one processor. The history information of the target resource comprises the presentation data of a plurality of information objects of the target resource in a history processing period, and the presentation data is used for representing the will of each information object to acquire the target resource in the corresponding history processing period.
In step S340, a plurality of candidate presentation data is determined by at least one processor. In an alternative implementation, the candidate presentation data may be determined according to a plurality of target presentation data corresponding to the target resource in a plurality of historical processing cycles. The target presentation data is the maximum value of the plurality of presentation data in the corresponding history processing cycle, that is, the presentation data of the information object bound to the target resource. In another alternative implementation, the at least one candidate presentation data may also be determined based on a historical presentation data range of the target information object.
Step S350, respectively taking each candidate presentation data as simulation presentation data of the target information object, and performing, by at least one processor, simulation of a history processing cycle according to history information of the target resource to determine simulation exposure data of each candidate presentation data. In an alternative implementation, in response to the candidate presentation data being determined as the target presentation data of the corresponding historical processing cycle, the simulated exposure parameters of the candidate presentation data in the corresponding historical processing cycle are obtained, the weighted sum of the simulated exposure parameters of the candidate presentation data in each historical processing cycle is calculated, and the simulated exposure data of the candidate presentation data is obtained.
And step S360, determining simulated click data corresponding to each candidate presentation data according to the simulated exposure data and the click parameters of the target information object. In an optional implementation manner, the product of each simulated exposure data and the click parameter of the target information object is calculated to obtain simulated click data corresponding to each candidate presentation data.
Step S370, sorting the simulated click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data.
And step S380, calculating the difference value of the simulation click data adjacent to each other respectively.
Step S390, determining the recommended presentation data from the candidate presentation data according to the difference.
According to the embodiment of the invention, the historical information of the target resource is obtained through the obtained identification of the target resource, the candidate display data are determined, the candidate display data are respectively used as the simulation display data of the target information object, the simulation of the historical processing period is carried out according to the historical information so as to determine the simulation exposure data of the candidate display data, and the recommended display data of the target information object is determined according to the simulation exposure data, so that the cost performance can be improved while the exposure parameter, the click parameter and the conversion parameter of the target information object are improved.
Fig. 4 is a flowchart of another information processing method according to an embodiment of the present invention. As shown in fig. 4, the information processing method according to the embodiment of the present invention includes the steps of:
step S410, receiving a data command from the client. Optionally, when the client needs to request to obtain the current presentation data, the data instruction is sent.
Step S420, analyzing the data command by at least one processor to obtain an identifier of the target resource.
Step S430, obtaining, by at least one processor, history information of the target resource according to the identifier of the target resource. The history information of the target resource comprises the presentation data of a plurality of information objects of the target resource in the history processing period, and the presentation data is used for representing the willingness of each information object to acquire the target resource in the corresponding history processing period.
In step S440, a plurality of candidate presentation data is determined by at least one processor. In an alternative implementation, the candidate presentation data may be determined according to a plurality of target presentation data corresponding to the target resource in a plurality of historical processing cycles. In another alternative implementation, the at least one candidate presentation data may also be determined based on a historical presentation data range of the target information object.
Step S450, respectively taking each candidate display data as simulation display data of the target information object, and performing simulation of a history processing period through at least one processor according to history information of the target resource to determine simulation exposure data of each candidate display data. In an alternative implementation, in response to the candidate presentation data being determined as the target presentation data of the corresponding historical processing cycle, the simulated exposure parameters of the candidate presentation data in the corresponding historical processing cycle are obtained, the weighted sum of the simulated exposure parameters of the candidate presentation data in each historical processing cycle is calculated, and the simulated exposure data of the candidate presentation data is obtained.
Step S460, determining first pre-recommendation data from the candidate presentation data according to each simulation exposure data. In an optional implementation manner, simulation click data corresponding to each candidate presentation data is determined according to click parameters of each simulation exposure data and a target information object, the simulation click data corresponding to each candidate presentation data is sorted according to the numerical values of a plurality of candidate presentation data, the difference values of two adjacent simulation click data are respectively calculated, and the first pre-recommendation data is determined from the candidate presentation data according to the difference values.
Step S470, determining second pre-recommendation data according to the history information of the target resource and the click parameter of the target information object. Optionally, the history information of the target resource further includes target presentation data in each history processing cycle, and a click parameter of an information object corresponding to each target presentation data. In an optional implementation manner, a product of the target presentation data in each history processing cycle and the click parameter of the corresponding information object is calculated to obtain a plurality of corresponding first parameters, a ratio of each first parameter to the click parameter of the target information object is calculated to obtain a plurality of corresponding pre-recommendation parameters, and an average value of the plurality of pre-recommendation parameters is calculated to obtain the second pre-recommendation data.
Step S480, recommending and presenting data of the target information object are determined according to the first pre-recommending data and the second pre-recommending data. In an optional implementation manner, a weighted sum of the first pre-recommended data and the second pre-recommended data is calculated according to a preset weight, so as to obtain recommended presentation data of the target information object.
It should be understood that the steps of acquiring the first pre-recommended data (steps S440 to S460) and the step of acquiring the second pre-recommended data (step S470) have no sequential execution relationship, and the execution order is not limited in this embodiment.
According to the embodiment of the invention, the historical information of the target resource is obtained through the obtained identification of the target resource, the first pre-recommendation data of the target information object is determined from the candidate display data according to the historical information of the target resource, the second pre-recommendation data of the target information object is determined according to the historical information of the target resource and the click parameter of the target information object, and the current display data of the target information object is determined according to the first pre-recommendation data and the second pre-recommendation data, so that the exposure parameter, the click parameter and the conversion parameter of the target information object can be improved, and meanwhile, the cost performance is improved.
Fig. 5 is a schematic diagram of an information processing apparatus of an embodiment of the present invention. As shown in fig. 5, the information processing apparatus of the embodiment of the present invention includes an instruction receiving unit 51, an identification acquiring unit 52, a history information acquiring unit 53, a candidate presentation data determining unit 54, a simulated exposure data determining unit 55, and a recommended presentation data determining unit 56.
The instruction receiving unit 51 is configured to receive a data instruction from a client. The identification acquisition unit 52 is configured to parse the data instructions through at least one processor to acquire an identification of the target resource. The history information obtaining unit 53 is configured to obtain, by at least one processor, history information of the target resource according to the identifier of the target resource, where the history information includes presentation data of a plurality of information objects of the target resource in a history processing cycle, and the presentation data is used to represent willingness of each information object to obtain the target resource in a corresponding history processing cycle. The candidate presentation data determination unit 54 is configured to determine, by the at least one processor, a plurality of candidate presentation data.
The simulated exposure data determination unit 55 is configured to perform simulation of a history processing cycle by at least one processor based on the history information to determine simulated exposure data of each candidate presentation data, with each candidate presentation data being simulated presentation data of a target information object, respectively.
In an alternative implementation, the simulated exposure data determination unit 55 includes a simulated exposure parameter determination subunit 551 and a simulated exposure data determination subunit 552.
The simulated exposure parameter determination subunit 551 is configured to, in response to the candidate presentation data being determined as the target presentation data of the corresponding history processing cycle, acquire the simulated exposure parameter of the candidate presentation data in the corresponding history processing cycle, the target presentation data being a maximum value among the plurality of presentation data in the corresponding history processing cycle. The simulated exposure data determination subunit 552 is configured to determine simulated exposure data of the candidate presentation data from simulated exposure parameters of the candidate presentation data in each historical processing cycle.
In an alternative implementation, the simulated exposure data determination subunit 552 includes a simulated exposure data determination module 5521. The simulated exposure data determination module 5521 is configured to calculate a weighted sum of simulated exposure parameters of the candidate presentation data in each historical processing cycle, and obtain simulated exposure data of the candidate presentation data.
The recommended presentation data determination unit 56 is configured to determine, by at least one processor, recommended presentation data for the target information object from the respective simulated exposure data.
In an alternative implementation, the recommended presentation data determining unit 56 includes a first sorting subunit 561, a first difference calculating subunit 562, and a first recommended presentation data determining subunit 563.
The first ordering subunit 561 is configured to order the simulated exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data. The first difference calculation sub-unit 562 is configured to calculate differences of two adjacent pairs of the simulated exposure data, respectively. The first recommended presentation data determining subunit 563 is configured to determine said recommended presentation data from said plurality of candidate presentation data in dependence on said difference.
In an alternative implementation, the recommended presentation data determination unit 56 includes a simulated click data determination subunit 564, a second ranking subunit 565, a second difference calculation subunit 566, and a second recommended presentation data determination subunit 567.
The simulated click data determination subunit 564 is configured to determine simulated click data corresponding to each candidate presentation data according to the each simulated exposure data and the click parameter of the target information object. The second sorting subunit 565 is configured to sort the simulated click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data. The second difference calculating subunit 566 is configured to calculate differences between two adjacent simulated click data, respectively. A second recommended presentation data determining subunit 567 is configured to determine the recommended presentation data from the plurality of candidate presentation data according to the difference.
In an alternative implementation, the recommended presentation data determining unit 56 includes a first pre-recommended data determining sub-unit 568, a second pre-recommended data determining sub-unit 569, and a third recommended presentation data determining sub-unit 56A.
The first pre-recommended data determination subunit 568 is configured to determine first pre-recommended data from the candidate presentation data according to the respective simulated exposure data. The second pre-recommendation data determining subunit 569 is configured to determine second pre-recommendation data according to the history information and the click parameter of the target information object. The third recommended presentation data determining subunit 56A determines the recommended presentation data of the target information object according to the first pre-recommended data and the second pre-recommended data.
In an alternative implementation, the third recommendation presentation data determining subunit 56A includes the recommendation presentation data module 56A 1. The recommended presentation data module 56a1 is configured to calculate a weighted sum of the first pre-recommended data and the second pre-recommended data according to a preset weight to obtain recommended presentation data of the target information object.
In an alternative implementation, the first pre-recommendation data determination subunit 568 includes a first ordering module 5681, a first difference calculation module 5682, and a first pre-recommendation data determination module 5683.
The first sorting module 5681 is configured to sort the simulated exposure data corresponding to each candidate presentation data according to the numerical value of the candidate presentation data. The first difference calculation module 5682 is configured to calculate differences of two adjacent pairs of the simulated exposure data, respectively. A first pre-recommendation data determination module 5683 is configured to determine the first pre-recommendation data from the plurality of candidate presentations based on the difference.
In an alternative implementation, the first pre-recommendation data determination subunit 568 includes a simulated click data determination module 5684, a second ranking module 5685, a second difference calculation module 5686, and a second pre-recommendation data determination module 5687.
The simulated click data determination module 5684 is configured to determine simulated click data corresponding to each candidate presentation data according to the simulated exposure data and the click parameter of the target information object. The second sorting module 5685 is configured to sort the simulated click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data. The second difference calculation module 5686 is configured to calculate differences between two adjacent simulated click data, respectively. The second pre-recommendation data determination module 5687 is configured to determine the first pre-recommendation data from the plurality of candidate presentations based on the difference.
In an optional implementation manner, the history information further includes target presentation data in each history processing cycle, and a click parameter of an information object corresponding to each target presentation data. The second pre-recommended data determination subunit 569 includes a first parameter calculation module 5691, a pre-recommended parameter calculation module 5692, and a second pre-recommended data acquisition module 5693.
The first parameter calculation module 5691 is configured to calculate a product of the target presentation data in each history processing cycle and the click parameter of the corresponding information object, respectively, to obtain a corresponding plurality of first parameters. The pre-recommendation parameter calculation module 5692 is configured to calculate a ratio of each first parameter to a click parameter of the target information object, so as to obtain a plurality of corresponding pre-recommendation parameters. The second pre-recommendation data acquisition module 5693 is configured to calculate an average value of the plurality of pre-recommendation parameters to acquire the second pre-recommendation data.
According to the embodiment of the invention, the historical information of the target resource is obtained through the obtained identification of the target resource, the candidate display data are determined, the candidate display data are respectively used as the simulation display data of the target information object, the simulation of the historical processing period is carried out according to the historical information so as to determine the simulation exposure data of the candidate display data, and the recommended display data of the target information object is determined according to the simulation exposure data, so that the cost performance can be improved while the exposure parameter, the click parameter and the conversion parameter of the target information object are improved.
Fig. 6 is a schematic diagram of an electronic device of an embodiment of the invention. In the present embodiment, the electronic device 6 includes a server, a terminal, and the like. As shown in fig. 6, the electronic apparatus 6: comprises at least one processor 601; and a memory 602 communicatively coupled to the at least one processor 601; and a communication component 603 communicatively coupled to the scanning device, the communication component 603 receiving and transmitting data under control of the processor 601; the memory 602 stores instructions executable by the at least one processor 601, and the instructions are executed by the at least one processor 601 to implement the information processing method.
Specifically, the electronic device includes: one or more processors 601 and a memory 602, one processor 601 being illustrated in fig. 6. The processor 601 and the memory 602 may be connected by a bus or other means, and fig. 6 illustrates an example of a connection by a bus. The memory 602, which is a non-volatile computer-readable storage medium, may be used to store non-volatile software programs, non-volatile computer-executable programs, and modules. The processor 601 executes various functional applications and data processing of the device, that is, implements the above-described information processing method, by executing nonvolatile software programs, instructions, and modules stored in the memory 602.
The memory 602 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store a list of options, etc. Further, the memory 602 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, the memory 602 may optionally include memory located remotely from the processor 601, which may be connected to an external device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more modules are stored in the memory 602, and when executed by the one or more processors 601, perform the information processing method in any of the method embodiments described above.
The product can execute the method provided by the embodiment of the application, has corresponding functional modules and beneficial effects of the execution method, and can refer to the method provided by the embodiment of the application without detailed technical details in the embodiment.
According to the embodiment of the invention, the historical information of the target resource is obtained through the obtained identification of the target resource, the candidate display data are determined, the candidate display data are respectively used as the simulation display data of the target information object, the simulation of the historical processing period is carried out according to the historical information so as to determine the simulation exposure data of the candidate display data, and the recommended display data of the target information object is determined according to the simulation exposure data, so that the cost performance can be improved while the exposure parameter, the click parameter and the conversion parameter of the target information object are improved.
Another embodiment of the invention is directed to a non-transitory storage medium storing a computer-readable program for causing a computer to perform some or all of the above-described method embodiments.
That is, as can be understood by those skilled in the art, all or part of the steps in the method for implementing the embodiments described above may be implemented by a program instructing related hardware, where the program is stored in a storage medium and includes several instructions to enable a device (which may be a single chip, a chip, or the like) or a processor (processor) to execute all or part of the steps of the method described in the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The embodiment of the invention discloses A1 and an information processing method, wherein the method comprises the following steps:
receiving a data instruction from a client;
analyzing the data instruction through at least one processor to obtain the identification of the target resource;
acquiring, by at least one processor, history information of the target resource according to the identifier of the target resource, where the history information includes presentation data of a plurality of information objects of the target resource in a history processing period, and the presentation data is used to represent willingness of each information object to acquire the target resource in a corresponding history processing period;
determining, by at least one processor, a plurality of candidate presentation data;
respectively taking the candidate presentation data as simulation presentation data of a target information object, and performing simulation of a historical processing period through at least one processor according to the historical information to determine simulation exposure data of the candidate presentation data;
determining, by at least one processor, recommended presentation data for the target information object based on the respective simulated exposure data.
The method according to a1 and a2, wherein the simulation of the history processing cycle by at least one processor according to the history information to determine the simulation exposure data of each candidate presentation data comprises:
in response to the candidate presentation data being determined to be target presentation data of a corresponding historical processing cycle, acquiring simulated exposure parameters of the candidate presentation data in the corresponding historical processing cycle, the target presentation data being a maximum value of a plurality of presentation data in the corresponding historical processing cycle;
and determining simulated exposure data of the candidate presentation data according to the simulated exposure parameters of the candidate presentation data in each historical processing period.
A3, the method of A2, wherein determining simulated exposure data for the candidate presentation data based on simulated exposure parameters of the candidate presentation data in each historical processing cycle comprises:
and calculating the weighted sum of the simulated exposure parameters of the candidate presentation data in each historical processing period to obtain the simulated exposure data of the candidate presentation data.
A4, the method of A1, wherein determining, by at least one processor, recommended presentation data for the target information object from the respective simulated exposure data includes:
sorting the simulation exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation exposure data adjacent to each other;
determining the recommended presentation data from the plurality of candidate presentation data based on the difference.
A5, the method of A1, wherein determining, by at least one processor, recommended presentation data for the target information object from the respective simulated exposure data includes:
determining simulated click data corresponding to each candidate presentation data according to the simulated exposure data and the click parameters of the target information object;
sorting the simulation click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation click data adjacent to each other;
determining the recommended presentation data from the plurality of candidate presentation data based on the difference.
A6, the method of A1, wherein determining, by at least one processor, recommended presentation data for the target information object from the respective simulated exposure data includes:
determining first pre-recommendation data from candidate presentation data according to the simulation exposure data;
determining second pre-recommendation data according to the historical information and the click parameters of the target information object;
and determining recommended presentation data of the target information object according to the first pre-recommended data and the second pre-recommended data.
A7, the method of A6, wherein the determining first pre-recommendation data from candidate presentation data according to the respective simulated exposure data includes:
sorting the simulation exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation exposure data adjacent to each other;
determining the first pre-recommendation data from the plurality of candidate presentation data according to the difference.
A8, the method of A6, wherein the determining first pre-recommendation data from candidate presentation data according to the respective simulated exposure data includes:
determining simulated click data corresponding to each candidate presentation data according to the simulated exposure data and the click parameters of the target information object;
sorting the simulation click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation click data adjacent to each other;
determining the first pre-recommendation data from the plurality of candidate presentation data according to the difference.
A9, the method according to A6, wherein the history information further includes target presentation data in each history processing period and click parameters of information objects corresponding to each target presentation data;
determining second pre-recommendation data according to the historical information and the click parameters of the target information object comprises:
calculating the product of the target presentation data in each history processing period and the click parameter of the corresponding information object to obtain a plurality of corresponding first parameters;
calculating the ratio of each first parameter to the click parameter of the target information object respectively to obtain a plurality of corresponding pre-recommendation parameters;
calculating an average value of the plurality of pre-recommendation parameters to obtain the second pre-recommendation data.
A10, the method of A6, wherein determining recommended presentation data of the target information object according to the first pre-recommendation data and the second pre-recommendation data includes:
and calculating the weighted sum of the first pre-recommended data and the second pre-recommended data according to a preset weight so as to obtain the recommended presentation data of the target information object.
The embodiment of the invention also discloses B1 and an information processing device, wherein the device comprises:
an instruction receiving unit configured to receive a data instruction from a client;
the identification acquisition unit is configured to analyze the data instruction through at least one processor to acquire the identification of the target resource;
a history information obtaining unit configured to obtain, by at least one processor, history information of the target resource according to the identifier of the target resource, where the history information includes presentation data of a plurality of information objects of the target resource in a history processing period, and the presentation data is used to represent willingness of each information object to obtain the target resource in a corresponding history processing period;
a candidate presentation data determination unit configured to determine, by at least one processor, a plurality of candidate presentation data;
the simulation exposure data determining unit is configured to respectively use each candidate presentation data as simulation presentation data of a target information object, and perform simulation of a history processing period according to the history information through at least one processor so as to determine simulation exposure data of each candidate presentation data;
a recommended presentation data determination unit configured to determine, by at least one processor, recommended presentation data for the target information object from the respective simulated exposure data.
B2, the apparatus according to B1, wherein the simulated exposure data determining unit includes:
a simulated exposure parameter determination subunit configured to, in response to the candidate presentation data being determined as target presentation data of a corresponding historical processing cycle, acquire a simulated exposure parameter of the candidate presentation data in the corresponding historical processing cycle, the target presentation data being a maximum value among a plurality of presentation data in the corresponding historical processing cycle;
and the simulated exposure data determining subunit is configured to determine simulated exposure data of the candidate presentation data according to the simulated exposure parameters of the candidate presentation data in each historical processing period.
B3, the apparatus of B2, wherein the simulated exposure data determining subunit comprises:
and the simulated exposure data determination module is configured to calculate the weighted sum of the simulated exposure parameters of the candidate presentation data in each historical processing period, and acquire the simulated exposure data of the candidate presentation data.
B4, the device according to B1, wherein the recommendation presentation data determining unit includes:
the first sequencing subunit is configured to sequence the simulation exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
a first difference calculation subunit configured to calculate differences of two adjacent pairs of the simulated exposure data, respectively;
a first recommended presentation data determining subunit configured to determine the recommended presentation data from the plurality of candidate presentation data according to the difference.
B5, the device according to B1, wherein the recommendation presentation data determining unit includes:
the simulated click data determining subunit is configured to determine simulated click data corresponding to each candidate presentation data according to each simulated exposure data and the click parameter of the target information object;
the second sorting subunit is configured to sort the simulation click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
the second difference calculation subunit is configured to calculate differences of the two adjacent simulated click data respectively;
a second recommended presentation data determining subunit configured to determine the recommended presentation data from the plurality of candidate presentation data according to the difference.
B6, the device according to B1, wherein the recommendation presentation data determining unit includes:
a first pre-recommendation data determination subunit configured to determine first pre-recommendation data from the candidate presentation data according to the respective simulated exposure data;
the second pre-recommendation data determining subunit is configured to determine second pre-recommendation data according to the historical information and the click parameters of the target information object;
and the third recommended presentation data determining subunit determines the recommended presentation data of the target information object according to the first pre-recommended data and the second pre-recommended data.
B7, the apparatus according to B6, wherein the first pre-recommendation data determining subunit comprises:
the first sequencing module is configured to sequence the simulation exposure data corresponding to each candidate presentation data according to the numerical value of the candidate presentation data;
the first difference calculation module is configured to calculate the difference of the two adjacent simulation exposure data respectively;
a first pre-recommendation data determination module configured to determine the first pre-recommendation data from the plurality of candidate presentation data according to the difference.
B8, the apparatus according to B6, wherein the first pre-recommendation data determining subunit comprises:
the simulation click data determining module is configured to determine simulation click data corresponding to each candidate presentation data according to each simulation exposure data and the click parameter of the target information object;
the second sorting module is configured to sort the simulation click data corresponding to each candidate presentation data according to the numerical value of the candidate presentation data;
the second difference calculation module is configured to calculate the difference between every two adjacent simulation click data respectively;
a second pre-recommendation data determination module configured to determine the first pre-recommendation data from the plurality of candidate presentation data according to the difference.
B9, the device according to B6, wherein the history information further includes target presentation data in each history processing period and click parameters of information objects corresponding to each target presentation data;
the second pre-recommendation data determination subunit includes:
the first parameter calculation module is configured to calculate the product of the target presentation data in each history processing period and the click parameter of the corresponding information object respectively so as to obtain a plurality of corresponding first parameters;
the pre-recommendation parameter calculation module is configured to calculate a ratio of each first parameter to a click parameter of the target information object to obtain a plurality of corresponding pre-recommendation parameters;
a second pre-recommendation data obtaining module configured to calculate an average value of the plurality of pre-recommendation parameters to obtain the second pre-recommendation data.
B10, the apparatus of B6, wherein the third recommendation presentation data determination subunit comprises:
and the recommendation presentation data module is configured to calculate a weighted sum of the first pre-recommendation data and the second pre-recommendation data according to a preset weight so as to obtain recommendation presentation data of the target information object.
The embodiment of the invention also discloses C1, an electronic device, comprising a memory and a processor, wherein the memory is used for storing one or more computer program instructions, and the processor executes the one or more computer program instructions to realize the method according to any one of A1-A10.
The embodiment of the invention also discloses D1, a computer readable storage medium, wherein the computer program instructions are stored on the computer readable storage medium, and when the computer program instructions are executed by a processor, the computer program instructions realize the method according to any one of A1-A10.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (10)

1. An information processing method, characterized in that the method comprises:
receiving a data instruction from a client;
analyzing the data instruction through at least one processor to obtain the identification of the target resource;
acquiring, by at least one processor, history information of the target resource according to the identifier of the target resource, where the history information includes presentation data of a plurality of information objects of the target resource in a history processing period, and the presentation data is used to represent willingness of each information object to acquire the target resource in a corresponding history processing period;
determining, by at least one processor, a plurality of candidate presentation data;
respectively taking the candidate presentation data as simulation presentation data of a target information object, and performing simulation of a historical processing period through at least one processor according to the historical information to determine simulation exposure data of the candidate presentation data;
determining, by at least one processor, recommended presentation data for the target information object based on the respective simulated exposure data.
2. The method of claim 1, wherein the determining, by the at least one processor, simulated exposure data for each candidate presentation data by simulating a historical processing cycle based on the historical information for simulated presentation data for each candidate presentation data targeting each candidate presentation data as an information object comprises:
in response to the candidate presentation data being determined to be target presentation data of a corresponding historical processing cycle, acquiring simulated exposure parameters of the candidate presentation data in the corresponding historical processing cycle, the target presentation data being a maximum value of a plurality of presentation data in the corresponding historical processing cycle;
and determining simulated exposure data of the candidate presentation data according to the simulated exposure parameters of the candidate presentation data in each historical processing period.
3. The method of claim 2, wherein determining simulated exposure data for the candidate presentation data based on simulated exposure parameters for the candidate presentation data in each historical processing cycle comprises:
and calculating the weighted sum of the simulated exposure parameters of the candidate presentation data in each historical processing period to obtain the simulated exposure data of the candidate presentation data.
4. The method of claim 1, wherein determining, by at least one processor, recommended presentation data for the target information object based on the respective simulated exposure data comprises:
sorting the simulation exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation exposure data adjacent to each other;
determining the recommended presentation data from the plurality of candidate presentation data based on the difference.
5. The method of claim 1, wherein determining, by at least one processor, recommended presentation data for the target information object based on the respective simulated exposure data comprises:
determining simulated click data corresponding to each candidate presentation data according to the simulated exposure data and the click parameters of the target information object;
sorting the simulation click data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation click data adjacent to each other;
determining the recommended presentation data from the plurality of candidate presentation data based on the difference.
6. The method of claim 1, wherein determining, by at least one processor, recommended presentation data for the target information object based on the respective simulated exposure data comprises:
determining first pre-recommendation data from candidate presentation data according to the simulation exposure data;
determining second pre-recommendation data according to the historical information and the click parameters of the target information object;
and determining recommended presentation data of the target information object according to the first pre-recommended data and the second pre-recommended data.
7. The method of claim 6, wherein determining first pre-recommendation data from candidate presentation data based on the simulated exposure data comprises:
sorting the simulation exposure data corresponding to each candidate presentation data according to the numerical values of the candidate presentation data;
respectively calculating the difference value of the simulation exposure data adjacent to each other;
determining the first pre-recommendation data from the plurality of candidate presentation data according to the difference.
8. An information processing apparatus characterized in that the apparatus comprises:
an instruction receiving unit configured to receive a data instruction from a client;
the identification acquisition unit is configured to analyze the data instruction through at least one processor to acquire the identification of the target resource;
a history information obtaining unit configured to obtain, by at least one processor, history information of the target resource according to the identifier of the target resource, where the history information includes presentation data of a plurality of information objects of the target resource in a history processing period, and the presentation data is used to represent willingness of each information object to obtain the target resource in a corresponding history processing period;
a candidate presentation data determination unit configured to determine, by at least one processor, a plurality of candidate presentation data;
the simulation exposure data determining unit is configured to respectively use each candidate presentation data as simulation presentation data of a target information object, and perform simulation of a history processing period according to the history information through at least one processor so as to determine simulation exposure data of each candidate presentation data;
a recommended presentation data determination unit configured to determine, by at least one processor, recommended presentation data for the target information object from the respective simulated exposure data.
9. An electronic device comprising a memory and a processor, wherein the memory is configured to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method of any of claims 1-7.
10. A computer-readable storage medium on which computer program instructions are stored, which computer program instructions, when executed by a processor, are to implement a method according to any one of claims 1-7.
CN202010152708.4A 2020-03-06 2020-03-06 Information processing method, information processing device, electronic equipment and computer readable storage medium Pending CN111460283A (en)

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