Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any inventive step based on the embodiments of the present disclosure, shall fall within the scope of protection of the present application.
Fig. 1 is a schematic diagram of a service publishing process related to the solution of the present specification in a practical application scenario. Supposing that a plurality of public opinion information exist in a media platform and are ranked according to the attention of the public opinion information, and a server crawls 2 public opinion information texts with the top attention ranking from the media platform; furthermore, regional information is extracted, and a topic of public opinion information is extracted by using an information classifier model obtained through pre-training. And issuing the service to be issued bound with each theme to the client side of the corresponding region through a preset issuing channel. For example, public opinion information with the first attention degree ranking is about the coming soaring of the room price in the city a, and the information with the topic of "room price" is extracted, and the service to be published which is bound with the information is "floor sales", so that the "floor sales" information can be published to the client side in the city a.
It should be noted that the service to be released may be understood as service information, a service product, and the like to be released. For example, the specific presentation manner may be that link information of the service to be published is displayed in an interactive interface of the client (e.g., a mobile phone). The publishing mode can be directly and automatically published by the system through APP (Application), or can be published through a media platform after manual or machine screening.
Based on the above-described scenarios, the following describes the embodiments of the present specification in detail.
Fig. 2 is a schematic flow chart of a service publishing method provided in an embodiment of this specification, where the method may specifically include the following steps:
step S202: and acquiring public opinion information.
The public opinion information may include: public sentiment information of a media platform, public sentiment information of a mobile phone APP and the like, and information with higher attention; this is merely an example and does not constitute a limitation on the type and source of public opinion information.
The method for acquiring the public opinion information can be used for crawling the required public opinion information from the media platform through a crawler technology. It is easy to understand that the way of obtaining public sentiment is not exactly the same for different information types and different information platforms, and the crawler technology is only used as an example. In practical application, technicians can select information acquisition technical means according to actual conditions.
Step S204: and determining regional information of the public opinion information, and extracting a theme contained in the public opinion information by using a pre-trained information classifier.
The public sentiment information provided by the media platform is text information, and certainly, the public sentiment information also comprises picture and audio and video information. The following description will be given taking text-type public opinion information as an example.
Some public opinion information contains rich information, and a plurality of themes can be extracted. For example, a public opinion information about the rising of the house price of the city a, the text of the public opinion information further includes: purchase limit policy information for the house holder's house, information for the limit of the first payment and loan of the house holder, and the like; thus, topics that may be extracted include: house price, house entrance, loan, city a.
The method for extracting the region information can be extracting after searching keywords from public sentiment information texts, and can also be extracting according to regional position source information of information distribution. The region information may be specific regional information such as province, city, and county, or may be national region information. When the region information cannot be confirmed or does not need to be confirmed, the region information can be defaulted to be nationwide; if the public opinion information occurs or is released in other countries of the world, the corresponding regional information can also be a plurality of countries of the world at the same time.
In the process of extracting the public opinion information theme, the workload is large, and the information classifier obtained through pre-training is adopted for extraction, so that the working efficiency of theme extraction can be effectively improved; especially, when a large amount of public opinion information needs to extract the theme, the high-efficiency working efficiency of the information classifier is more obvious.
Step S206: and determining the service to be issued matched with the public opinion information according to the type of the theme.
In practical application, the service to be published is published through a specified publishing channel. The publishing channel can be understood as a way or a platform for publishing the service to be published. The service to be issued can be understood as product information to be marketed, including product names and details, link information obtained by the product information, and the like; such as building sales information, payment APP promotional information, loan information, and so forth.
As can be seen from the foregoing, a plurality of topics can be included for the same public opinion information. In an actual popularization process, in order to obtain a better popularization effect, corresponding marketing tools or distribution channels need to be selected for different topic types. For example, for the topic of "loan" class, the corresponding service to be issued may be "loan service to be done", "fast loan service with low interest rate"; the release channel can be a popularization channel related to money, such as 'bank mobile phone APP', payment software and the like.
Step S208: and issuing the service to be issued based on the region information.
In order to obtain better publishing and marketing effects, the service to be published may be a scheme capable of solving problems brought by public opinion information for consumers.
Supposing that the public opinion information is 'a case of occurrence of a fire in a caregiver in city a', the extracted theme is 'fire', and in order to ensure the property safety of consumers, the corresponding service to be released can be 'insurance', 'financing', and other related information. The marketing tool is assumed to be payment software, and the specific launching mode can be as follows:
one way is as follows: the method comprises the steps that a 'property insurance' (namely, a service to be released) is released aiming at a 'payment success page' (namely, a release channel) of client payment software of a user in the market A;
in another mode: the "wallet home page" (i.e., the distribution channel) for the client payment software for the users in city a reveals "property insurance" (i.e., the traffic to be distributed).
Through the embodiment, after the public opinion information is crawled, the public opinion information is analyzed, the regional information carried by the public opinion information is extracted, and meanwhile, the topic of the public opinion information is extracted by using the information classifier, so that the regional information and the topic can be extracted more quickly; furthermore, according to the region information, the service to be published bound with the public sentiment information theme can be delivered to the client side of the region, so that a more accurate delivery effect is achieved.
In one or more embodiments of the present specification, the pre-training of the information classifier specifically may include: extracting word vectors in the public opinion information; clustering the word vectors; determining a theme corresponding to the word vector according to the clustering result; and training to obtain the information classifier according to the theme and the corresponding public opinion information text.
For example, as shown in fig. 3, a schematic diagram of an information classifier training process provided in the embodiment of the present application specifically includes:
compressing the public sentiment information text by using a TF-IDF (Term Frequency-Inverse Document Frequency) algorithm to obtain a corresponding word vector, and performing cluster analysis on the obtained word vector; after the clustering analysis is performed, a topic represented by a plurality of word vectors is obtained, and further, a topic is extracted from the distribution of each topic word vector by using an LDA (Latent Dirichlet Allocation, document topic generation model) model; extracting a word from the word vector corresponding to the extracted subject; repeating the above process until each word in the word vector is traversed; then, the first few subject words are extracted.
In order to obtain a better classification effect, the extracted topics need to be further screened manually, and then corresponding public opinion information texts are input to train an information classifier model. In addition, in order to improve the screening efficiency, the screening may be performed by using a machine learning model.
Because public opinion information has higher timeliness requirements, generally, the public opinion information has higher attention degree in the first few days of release, and after a period of time or other new public opinion information appears, the attention degree of the previous public opinion information is rapidly reduced. Therefore, the marketing effect is directly influenced based on the speed of the theme extraction of the public opinion information, and the information classifier is utilized in the embodiment of the application, so that the efficiency of the theme extraction of the public opinion information can be higher.
In one or more embodiments of the present specification, determining, according to the type of the topic, a service to be published that matches the public opinion information may specifically include: according to the corresponding relation between the pre-established theme and the service to be issued; determining corresponding service to be published as the service to be published matched with the public opinion information aiming at the determined type of the theme; wherein, the service to be issued includes: and (5) service products to be released.
It should be noted that, as described above, the same public opinion information may include a plurality of topic types. The theme and the service to be issued are in a many-to-many relationship. For example, the service products to be released are: the promotional products of the bank loan, the corresponding subject may include: house, car, shopping, loan, interest rate, etc., when extracted about the above topics for public opinion information, the promotional product of the "bank loan" may be issued.
In one or more embodiments of the present specification, the issuing the service to be issued based on the region information may specifically include: issuing the service to be issued to a client terminal positioned in the region designated by the region information through a designated issuing channel; the publishing channel is preset for publishing a plurality of services to be published.
The client can be a mobile phone, a computer and other devices which can be used for receiving and displaying the service to be released. Aiming at different clients, the adopted publishing channels can be published through a mobile phone APP or a television media platform. The distribution channel and the service to be distributed may also be in a many-to-many relationship, and the corresponding relationship between the distribution channel and the type of the service to be distributed may be preset.
It should be noted that, all the clients have location information, and assuming that the client receiving the service to be distributed is a mobile phone, the location information of the client may be obtained based on GPS, or based on base station positioning of the mobile operating network, or obtained according to a historical activity track (for example, a frequently consumed area) of the client. Further, the region information to which the user client belongs is determined according to the activity rule of the client held by the user.
In one or more embodiments of the present description, the issuing, through a specified issuing channel, a service to be issued to a client located in a specified area of the area information may specifically include: determining interest points of a client; establishing an interest relationship between the client and the theme based on the interest point of the client; and according to the interest relation, issuing the service to be issued aiming at the public opinion information to an appointed client through an appointed issuing channel.
In order to realize more accurate marketing, the interest points carried by the client are further extracted on the basis of determining the theme and the regional information of the public sentiment information. The interest points may be keywords recently searched or focused by the user, such as: house, car, loan, etc.
For example, if public opinion information is that the rate of a house will suddenly drop in a city a, a user a in the city a frequently searches for the rate of a house through a search engine installed on a mobile phone client, and the point of interest of the user a is "rate of a house". And the user B in the city B searches the working post in the city A and the room price information in the city A through the mobile phone client. Then, the interest points of the user B are 'A city' and 'house price', and when the service to be released is released, the service to be released of 'building' can be simultaneously released to the user A and the user B, so that a more accurate effect of releasing the service to be released based on the regional information can be obtained.
In one or more embodiments of the present specification, before publishing the service to be published, the method further includes: screening the subject; issuing the service to be issued may specifically include: and issuing the service to be issued matched with the public opinion information subjected to topic screening through the issuing channel.
In order to ensure that the published service to be published is matched with the real-time public opinion information, the theme can be screened manually or mechanically before being published. And after the service is screened, issuing the service to be issued by utilizing a pre-specified issuing channel. The result of this screening can feed back the theme screening link, adjusts the corresponding relation of theme and public opinion information text, carries out the training after rejecting the inaccurate theme, is favorable to improving the training effect to information classifier for information classifier has more accurate classification result.
Based on the embodiment, after the public opinion information is crawled, the public opinion information is analyzed, the regional information carried by the public opinion information is extracted, and meanwhile, the topic of the public opinion information is extracted by using the information classifier, so that the regional information and the topic can be extracted more quickly; furthermore, according to the region information, the service to be published bound with the public sentiment information theme can be delivered to the client side of the region, so that a more accurate delivery effect is achieved.
In order to better understand the technical solution of the present application, an embodiment of the present specification further provides a schematic diagram of a service publishing framework, where the schematic diagram includes a process of publishing a service to be published and training a classifier.
As shown in fig. 4, the public opinion information acquisition system includes data sources, such as a microblog, a media platform, and the like, and acquires public opinion information by using a crawler technology. Further, public sentiment information is analyzed, the analysis process mainly comprises two parts, one part is to extract regional information based on the public sentiment information, the other part is to classify a plurality of theme classifications aiming at the public sentiment information by using an information classifier, and the corresponding service to be published is determined according to the preset binding relationship between the theme and the service to be published. And auditing the service to be issued and the corresponding subject through staff in the appointed region, and issuing the approved service to be issued on line.
The off-line processing process of public opinion information is as follows: analyzing the off-line public opinion information, and obtaining a plurality of subjects by using a TF-IDF algorithm and clustering analysis; and further extracting the first topics by using an LDA algorithm, screening the topics by staff to obtain topics suitable for operation, training by using the main bodies and corresponding public opinion information texts, and associating and binding the topics and the service to be published. And obtaining a proper information classifier.
Based on the same idea, an embodiment of the present specification further provides a service publishing device, as shown in fig. 5, where the device specifically includes:
the acquisition module 501 acquires public opinion information;
an extraction module 502, which determines regional information of the public opinion information and extracts a theme contained in the public opinion information by using a pre-trained information classifier;
the matching module 503 determines the service to be published matched with the public opinion information according to the type of the theme;
the issuing module 504 issues the service to be issued according to the region information.
Further, the extracting module 502 includes the information classifier, pre-training the information classifier, and the training process specifically includes:
extracting word vectors in the public opinion information text;
clustering the word vectors;
determining the theme corresponding to the word vector after the clustering analysis is finished;
and training to obtain the information classifier based on the theme determined by screening and the corresponding public opinion information text.
Further, the matching module 503 determines, according to the type of the topic, a service to be published that is matched with the public opinion information, and specifically may include:
the matching module 503 pre-establishes a corresponding relationship between the theme and the service to be issued;
according to the corresponding relation, calling a corresponding publishing channel aiming at the determined type of the theme; the publishing channel is preset for publishing a plurality of services to be published.
Further, the apparatus further comprises: a screening module 505;
before the publishing module 504 publishes the service to be published through the designated publishing channel:
the screening module 505 screens the topic;
and publishing the service to be published aiming at the public opinion information obtained by screening through the specified publishing channel.
Further, the apparatus further comprises:
the publishing module 504 is configured to publish the service to be published for the public opinion information to a specified client through a specified publishing channel; wherein the designated client is located in the region designated by the region information.
Further, the publishing module 504 publishes the service to be published for the public opinion information to a specified client through a specified publishing channel; the method includes that the designated client is located in a designated region of the region information, and specifically includes:
establishing an interest relationship between the client and the theme based on the interest points carried by the client;
and according to the interest relation, issuing the service to be issued aiming at the public opinion information to an appointed client through an appointed issuing channel.
Based on the same idea, an embodiment of this specification further provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to:
public opinion information is obtained;
determining regional information of the public opinion information, and extracting a theme contained in the public opinion information by using a pre-trained information classifier;
determining a service to be issued matched with the public opinion information according to the type of the theme;
and issuing the service to be issued based on the region information.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the embodiments of the apparatus, the electronic device, and the nonvolatile computer storage medium, since they are substantially similar to the embodiments of the method, the description is simple, and the relevant points can be referred to the partial description of the embodiments of the method.
The apparatus, the electronic device, the nonvolatile computer storage medium and the method provided in the embodiments of the present description correspond to each other, and therefore, the apparatus, the electronic device, and the nonvolatile computer storage medium also have similar advantageous technical effects to the corresponding method.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the various elements may be implemented in the same one or more software and/or hardware implementations in implementing one or more embodiments of the present description.
As will be appreciated by one skilled in the art, the present specification embodiments may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein.
The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
This description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present specification, and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.