CN113516491B - Popularization information display method and device, electronic equipment and storage medium - Google Patents
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Abstract
The application discloses a popularization information display method, a popularization information display device, electronic equipment and a storage medium, and relates to the technical field of advertisements. The specific implementation scheme is as follows: acquiring user intention; inquiring target popularization information matched with the user intention; combining the set guide language with the user intention to obtain a popularization guide element; according to the method, the user intention is deeply identified and displayed in the target popularization information by the popularization guide element, so that the relevance between the target popularization information and the user requirement is emphasized, the understandability of the target popularization information is enhanced, and the user experience is improved. Meanwhile, the method is applied to large-search commercial products, so that the click rate of target popularization information results can be improved, and the rendering efficiency of a commercial system is further improved.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to the field of advertisement technologies, and in particular, to a method and apparatus for displaying promotion information, an electronic device, and a computer readable storage medium.
Background
At present, in the search field, for example, knowledge pages such as hundred degrees of knowledge and hundred degrees of experience, the exposure information of commercial advertisements emphasizes the attribute of the advertisement, the relevance of the advertisement and the intention of a user is not fully reflected, the benefit of the deep intention of the user is not reflected, and the advertisement display efficiency is reduced.
Disclosure of Invention
Provided are a method, an apparatus, an electronic device, and a computer-readable storage medium for promotional information presentation.
According to the first aspect, a popularization information display method is provided, and through deeply identifying user intention, the user intention is displayed in the target popularization information in the form of popularization guide elements, so that the relevance between the target popularization information and user requirements is emphasized, the understandability of the target popularization information is enhanced, and the user experience is improved. Meanwhile, the method is applied to large-search commercial products, so that the click rate of target popularization information results can be improved, and the rendering efficiency of a commercial system is further improved.
The second aspect of the application provides a popularization information display device.
A third aspect of the application proposes an electronic device.
A fourth aspect of the present application is directed to a non-transitory computer-readable storage medium storing computer instructions.
A fifth aspect of the application proposes a computer program product.
An embodiment of a first aspect of the present application provides a popularization information display method, including: acquiring user intention; inquiring target popularization information matched with the user intention; combining a set guide language with the user intention to obtain a popularization guide element; and inserting the promotion guide element into the target promotion information for display.
According to the popularization information display method, the intention of the user is obtained; inquiring target popularization information matched with the user intention; combining a set guide language with the user intention to obtain a popularization guide element; and inserting the promotion guide element into the target promotion information for display. According to the method, the user intention is deeply identified and displayed in the target popularization information in the form of the popularization guide element, so that the relevance between the target popularization information and the user requirement is emphasized, the comprehensibility of the target popularization information is enhanced, and the user experience is improved. Meanwhile, the method is applied to large-search commercial products, so that the click rate of target popularization information results can be improved, and the rendering efficiency of a commercial system is further improved.
An embodiment of a second aspect of the present application provides a promotional information display apparatus, including: the acquisition module is used for acquiring the intention of the user; the query module is used for querying target popularization information matched with the user intention; the combination setting module is used for combining and setting the guide language and the user intention to obtain a popularization guide element; and the display module is used for inserting the promotion guide element into the target promotion information for display.
An embodiment of a third aspect of the present application provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, so that the at least one processor can execute the promotion information presentation method according to the embodiment of the first aspect of the present application.
An embodiment of a fourth aspect of the present application proposes a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the promotion information presentation method according to the embodiment of the first aspect of the present application.
An embodiment of a fifth aspect of the present application proposes a computer program product comprising a computer program which, when executed by a processor, implements the steps of the promotional information presentation method according to an embodiment of the first aspect of the present application.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are included to provide a better understanding of the present application and are not to be construed as limiting the application. Wherein:
FIG. 1 is a schematic diagram of a first embodiment according to the present application;
FIG. 2 is a schematic illustration of a promotional guidance element presentation of an embodiment of the present application;
FIG. 3 is a schematic diagram of a second embodiment according to the present application;
FIG. 4 is a schematic diagram of a third embodiment according to the present application;
FIG. 5 is a schematic diagram of a fourth embodiment according to the application;
FIG. 6 is a schematic diagram of a fifth embodiment according to the present application;
FIG. 7 is a schematic diagram of a sixth embodiment according to the application;
fig. 8 is a schematic view of a seventh embodiment according to the present application;
fig. 9 is a block diagram of an electronic device for implementing a promotional information presentation method of an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present application will now be described with reference to the accompanying drawings, in which various details of the embodiments of the present application are included to facilitate understanding, and are to be considered merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The following describes a popularization information display method, a device, an electronic device and a computer readable storage medium according to an embodiment of the present application with reference to the accompanying drawings.
Fig. 1 is a schematic diagram according to a first embodiment of the present application.
As shown in fig. 1, the specific implementation process of the popularization information display method is as follows:
step 101, obtaining user intention.
In the embodiment of the application, the directed graph can be generated through the searching behavior of the user, the trained graph neural network model is adopted to generate the intention representation vector of each node in the directed graph, and the intention of the user is determined according to the intention representation vector of each node in the directed graph, and the detailed description of the subsequent embodiment is described in detail. Wherein the user intent may be a user's demand, a user's preference, etc.
Step 102, inquiring target popularization information matched with the user intention.
Optionally, text matching is performed between the user intention and the title and/or content of the candidate popularization information; according to the text matching degree, determining seed information from candidate popularization information; and taking the seed information and promotion information similar to the seed information as target promotion information.
That is, the user intention may be text-matched with the titles and/or contents of the plurality of candidate popularization information using a text similarity algorithm, and at least one piece of seed information may be determined from the plurality of candidate popularization information according to the text matching degree, for example, candidate popularization information having a higher text similarity with the user intention may be used as the seed information. Further, a search space is built based on the seed information, popularization information similar to the seed information is obtained, and then the seed information and the popularization information similar to the seed information are used as target popularization information. The candidate promotion information may be promotion information in a promotion information database. Therefore, text matching is carried out on the user intention and the titles and/or the contents of the candidate popularization information, at least one piece of seed information is determined from the candidate popularization information, and the user intention can cover more popularization information.
And 103, combining the set guide language with the user intention to obtain the popularization guide element.
In order to enable the user intention to be displayed in the form of a label element and to be capable of popularizing and guiding the target popularizing information, in the embodiment of the application, the set guide language and the user intention can be combined to obtain the popularizing and guiding element. The set guide language can be a word which plays a role in guiding the popularization information. For example, the user intends to pay attention to the radiation-proof eyes, and the corresponding popularization guide elements can be obtained by combining the set guide words and the user intent, so that people paying attention to the radiation-proof eyes can see the radiation-proof eyes, and popularization information for treating myopia can be popularized and guided.
It may be understood that, in order to make the semantics of the promotion guidance element smoother and better understand the promotion information, in the embodiment of the present application, a plurality of candidate guidance languages may be preset, the user intention may be combined with each candidate guidance language, the candidate guidance language with higher semantic smoothness with the user intention may be selected as the set guidance language, that is, the plurality of candidate guidance languages may be respectively combined and compared with the user intention, where the promotion information may be guided, and the candidate guidance language with smoother semantic combination with the user intention may be selected as the set guidance language.
And 104, inserting the promotion guidance element into the target promotion information for display.
In order to emphasize the relevance of the target popularization information and the user requirement, the comprehensibility of the target popularization information is enhanced, and the user experience is improved. In the embodiment of the application, a feature extraction algorithm can be adopted to extract the promotion title and promotion content from the target promotion information, promotion guide elements are inserted between the promotion title and promotion content, and the target promotion information inserted with the promotion guide elements is displayed.
It can be appreciated that, in order to make the promotion guidance element better be displayed as a component of promotion content, in the embodiment of the present application, before the promotion guidance element is inserted between the promotion title and promotion content, the font format of the promotion guidance element may be set according to the font format of the promotion content. For example, the font format of the promotion content is "Song Ti, no. four", and the font size of the font of the promotion guidance element may be set to "Song Ti, no. five".
For example, as shown in fig. 2, the promotion guidance element in the block of fig. 2 is inserted between the promotion title and the promotion content, and the promotion guidance element font format is set according to the font of the promotion content, and the promotion guidance element is displayed as an integral part of the promotion content.
In conclusion, through deeply identifying the user intention, the relevance of the target popularization information and the user requirement is emphasized, the comprehensibility of the target popularization information is enhanced, and the user experience is improved. Meanwhile, the method is applied to large-search commercial products, so that the click rate of target popularization information results can be improved, and the rendering efficiency of a commercial system is further improved.
As shown in fig. 3, fig. 3 is a schematic diagram according to a second embodiment of the present application. In the embodiment of the application, the directed graph can be generated through the searching behavior of the user, the intention representation vector of each node in the directed graph is generated by adopting a trained graph neural network model, and the intention of the user is determined according to the intention representation vector of each node in the directed graph, and the specific implementation process is as follows:
step 301, generating a directed graph according to each search behavior; the nodes in the directed graph are used for indicating keywords related to each search behavior; the directed edges in the directed graph are used for connecting the nodes, and the direction of the directed edges indicates the execution sequence of each search behavior.
In order to determine the user intention more accurately according to the search behavior of the user, in the embodiment of the application, the search behavior of the user can be modeled through natural language technology processing, wherein nodes in the directed graph are used for indicating keywords related to each search behavior; the directed edges in the directed graph are used for connecting the nodes, and the direction of the directed edges indicates the execution sequence of each search behavior.
Step 302, generating an intention representation vector of each node in the directed graph by using the trained graph neural network model.
The directed graph constructed from the user's search behavior may then be input into a trained graph neural network model, and intent characterization vectors for each node in the directed graph may be generated. In the embodiment of the application, the graph neural network model is trained by the data of the historical search behavior of the user and evaluated by the test set, and is optimized and trained for multiple times, so that the graph neural network model finally achieves a certain accuracy rate.
Step 303, determining the user intention according to the intention characterization vector of each node in the directed graph.
Alternatively, as shown in fig. 4, fig. 4 is a schematic diagram according to a third embodiment of the present application. In the embodiment of the application, each search behavior is divided according to the time interval of each search behavior, then each node belonging to the same group of search sessions is subjected to intention characterization vector weighted fusion, and then the user intention of each group of search sessions is generated. The specific implementation process is as follows:
Step 401, dividing each search behavior into at least one group of search sessions according to the execution time interval of each search behavior.
In order to divide the search behavior into units for processing, in the embodiment of the present application, the search behavior may be divided according to the execution interval of each search behavior of the user, so as to obtain at least one group of search sessions.
Step 402, carrying out intention characterization vector weighted fusion on all nodes belonging to the same group of search sessions to obtain an intention characterization vector of a corresponding search session; the weight of each node is determined according to the similarity of the intention characterization vector of the corresponding node and the last node in the same group of search sessions.
Then, different search sessions belonging to the same execution interval are used as the same group of search sessions, and in order to make the intention characterization vectors of the search sessions more balanced and reasonable, in the embodiment of the application, each node of the same group of search sessions can be subjected to weighted fusion of the intention characterization vectors to obtain the intention characterization vectors of the corresponding search sessions. It should be noted that, since the similarity of the intent representation vector of the last node can best represent the intent representation vector of the search session, the weight of each node is determined according to the similarity of the corresponding node and the intent representation vector of the last node in the same group of search sessions.
Step 403, generating user intention of each group of search session according to intention characterization vector of each group of search session.
Optionally, obtaining a plurality of intention core words; wherein, each intention core word is extracted from keywords related to each search behavior; for each set of search sessions, determining user intent from the plurality of intent core words according to the degree of intent characterization vector similarity between each intent core word and the corresponding search session; wherein the intent characterization vector is similar to a degree indicating a confidence level of the corresponding user intent.
That is, the intended core word may be extracted from the keywords related to each search behavior, thereby obtaining a plurality of intended core words; then, for each group of search sessions, from among the plurality of intention core words, the similarity degree of the intention characterization vector between each intention core word and the corresponding search session can be calculated according to a text similarity algorithm, so as to determine the user intention, for example, the top N (for example, 3) intention core words with higher similarity degree with the intention characterization vector of the search session can be used as the user intention. It should be noted that, the similarity degree of the intent characterization vector can be used to indicate the confidence level of the corresponding user intent. For example, the higher the similarity of the intent characterization vectors, the higher the confidence level representing the corresponding user intent, and the higher the user confidence level, the corresponding intent core word is closer to the user intent, so that the user intentions of each group of search sessions can be filtered according to the confidence level of the user intentions.
Therefore, the searching behavior of the user predicts the user intention through the graphic neural network, the user intention is combined with the set guide language, when the target popularization information is similar to the user intention, the user intention is displayed in the target popularization information in the form of popularization guide elements, the relevance between the target popularization information and the user intention is reflected, the psychological acceptance of the user is enhanced, the user is helped to simultaneously promote the click rate of the target popularization information, and the system rendering efficiency is optimized.
According to the popularization information display method, the intention of the user is obtained; inquiring target popularization information matched with the user intention; combining the set guide language with the user intention to obtain a popularization guide element; the popularization guide elements are inserted into the target popularization information for display, and through deep recognition of the user intention, when the target popularization information is similar to the user intention, the user intention is displayed in the target popularization information in the form of the popularization guide elements, so that the relevance between the target popularization information and the user requirement is emphasized, the comprehensiveness of the target popularization information is enhanced, and the user experience is improved. Meanwhile, the method is applied to large-search commercial products, so that the click rate of target popularization information results can be improved, and the rendering efficiency of a commercial system is further improved.
In order to implement the embodiments shown in fig. 1 to fig. 4, the embodiment of the application further provides a popularization information display device.
Fig. 5 is a schematic diagram according to a fourth embodiment of the present application. As shown in fig. 5, the promotion information apparatus 500 includes: the system comprises an acquisition module 510, a query module 520, a combination module 530 and a presentation module 540.
Wherein, the obtaining module 510 is configured to obtain a user intention; a query module 520, configured to query target popularization information matched with the user intention; a combination module 530, configured to combine the set guide language with the user intention to obtain a promotion guide element; and the display module 540 is used for inserting the promotion guidance element into the target promotion information for display.
As a possible implementation manner of the embodiment of the present application, on the basis of fig. 5, as shown in fig. 6, the presentation module 540 includes: extraction unit 541, insertion unit 542, and presentation unit 543.
Wherein, the extracting unit 541 is configured to extract a promotion title and promotion content from the target promotion information; an inserting unit 542 for inserting a promotion guidance element between a promotion title and promotion content; and the display unit 543 is used for displaying the target promotion information inserted with the promotion guidance element.
As a possible implementation manner of the embodiment of the present application, on the basis of fig. 6, as shown in fig. 7, the display module further includes: a setting unit 544.
Wherein, the setting unit 544 is configured to set a font format of the promotion guidance element according to the font format of the promotion content.
As one possible implementation manner of the embodiment of the present application, the obtaining module 510 is specifically configured to generate a directed graph according to each search behavior; the nodes in the directed graph are used for indicating keywords related to individual searching behaviors; the directed edges in the directed graph are used for connecting all nodes, and the direction of the directed edges indicates the execution sequence of all search behaviors; generating an intention representation vector of each node in the directed graph by adopting a trained graph neural network model; and determining the user intention according to the intention representation vector of each node in the directed graph.
As a possible implementation manner of the embodiment of the present application, the obtaining module 510 is specifically configured to divide each search behavior into at least one group of search sessions according to an execution time interval of each search behavior; carrying out the weighted fusion of the intention token vectors on all nodes belonging to the same group of search sessions to obtain the intention token vector of the corresponding search session; the weight of each node is determined according to the similarity of the intention characterization vector of the corresponding node and the last node in the same group of search sessions; the user intent for each set of search sessions is generated from the intent characterization vectors for the sets of search sessions.
As one possible implementation manner of the embodiment of the present application, the obtaining module 510 is specifically configured to obtain a plurality of intent core words; wherein, each intention core word is extracted from keywords related to each search behavior; for each set of search sessions, determining user intent from the plurality of intent core words according to the degree of intent characterization vector similarity between each intent core word and the corresponding search session; the intention characterization vector similarity is used for indicating the confidence level of the intention of the corresponding user; after generating the user intent for each set of search sessions, further comprising: the user intent of each set of search sessions is filtered based on the confidence level.
As a possible implementation manner of the embodiment of the present application, on the basis of fig. 7, as shown in fig. 8, the popularization information display apparatus further includes: a module 550 is selected.
The selection module 550 is configured to select a set guide from the candidate guides according to semantic fluency between the user intention and the candidate guides.
As one possible implementation manner of the embodiment of the present application, the query module 520 is specifically configured to perform text matching on the user intention and the title and/or content of the candidate popularization information; according to the text matching degree, determining seed information from candidate popularization information; and taking the seed information and promotion information similar to the seed information as target promotion information.
According to the popularization information display device, the intention of the user is obtained; inquiring target popularization information matched with the user intention; combining the set guide language with the user intention to obtain a popularization guide element; the popularization guide elements are inserted into the target popularization information for display, and through deep recognition of the user intention, when the target popularization information is similar to the user intention, the user intention is displayed in the target popularization information in the form of the popularization guide elements, so that the relevance between the target popularization information and the user requirement is emphasized, the comprehensiveness of the target popularization information is enhanced, and the user experience is improved. Meanwhile, the method is applied to large-search commercial products, so that the click rate of target popularization information results can be improved, and the rendering efficiency of a commercial system is further improved.
According to an embodiment of the present application, there is also provided a computer program product including a computer program which, when executed by a processor, implements the steps of the promotion information presentation method described in the above embodiment.
According to an embodiment of the present application, the present application also provides an electronic device and a readable storage medium.
As shown in fig. 9, a block diagram of an electronic device according to a promotional information presentation method according to an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the applications described and/or claimed herein.
As shown in fig. 9, the electronic device includes: one or more processors 901, memory 902, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the electronic device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In other embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple electronic devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). In fig. 9, a processor 901 is taken as an example.
Memory 902 is a non-transitory computer readable storage medium provided by the present application. The memory stores instructions executable by at least one processor to cause the at least one processor to execute the promotional information presentation method provided by the present application. The non-transitory computer-readable storage medium of the present application stores computer instructions for causing a computer to execute the promotion information presentation method provided by the present application.
The memory 902 is used as a non-transitory computer readable storage medium, and may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules (e.g., the acquisition module 510, the query module 520, the combination module 530, and the presentation module 540 shown in fig. 5) corresponding to the promotion information presentation method according to the embodiments of the present application. The processor 901 executes various functional applications of the server and data processing by running non-transitory software programs, instructions, and modules stored in the memory 902, that is, implements the promotion information presentation method in the above-described method embodiment.
The memory 902 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created from the use of the electronic device exposed by the promotional information, and the like. In addition, the memory 902 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory 902 optionally includes memory remotely located relative to the processor 901, which may be connected to the promotional information presentation electronic 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.
The electronic device for promoting the information display method may further include: an input device 903 and an output device 904. The processor 901, memory 902, input devices 903, and output devices 904 may be connected by a bus or other means, for example in fig. 9.
The input device 903 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device presented with promotional information, such as a touch screen, keypad, mouse, trackpad, touchpad, pointer stick, one or more mouse buttons, trackball, joystick, and the like. The output means 904 may include a display device, auxiliary lighting means (e.g., LEDs), tactile feedback means (e.g., vibration motors), and the like. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device may be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASIC (application specific integrated circuit), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
These computing programs (also referred to as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present application may be performed in parallel, sequentially, or in a different order, provided that the desired results of the disclosed embodiments are achieved, and are not limited herein.
The above embodiments do not limit the scope of the present application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the scope of the present application.
Claims (15)
1. The popularization information display method is characterized by comprising the following steps of:
Acquiring user intention;
Inquiring target popularization information matched with the user intention;
Combining a set guide language with the user intention to obtain a popularization guide element;
inserting the promotion guidance element into the target promotion information for display;
The obtaining the user intention includes:
Generating a directed graph according to each search behavior; the nodes in the directed graph are used for indicating keywords related to each search behavior; the directional edges in the directional graph are used for connecting all nodes, and the direction of the directional edges indicates the execution sequence of all search behaviors;
generating an intention representation vector of each node in the directed graph by adopting a trained graph neural network model;
Dividing each search behavior into at least one group of search sessions according to the execution time interval of each search behavior;
carrying out the weighted fusion of the intention token vectors on all nodes belonging to the same group of search sessions to obtain the intention token vector of the corresponding search session; the weight of each node is determined according to the similarity of the intention characterization vector of the corresponding node and the last node in the same group of search sessions;
the user intent for each set of search sessions is generated from the intent characterization vectors for the sets of search sessions.
2. The promotion information presentation method according to claim 1, wherein the inserting the promotion guidance element into the target promotion information for presentation includes:
extracting popularization titles and popularization contents from the target popularization information;
Inserting the promotion guidance element between the promotion header and the promotion content;
and displaying the target promotion information inserted into the promotion guide element.
3. The promotion information presentation method according to claim 2, wherein before the promotion guidance element is inserted between the promotion title and the promotion content, further comprising:
And setting the font format of the promotion guide element according to the font format of the promotion content.
4. The promotional information presentation method of claim 1, wherein said generating the user intent for each set of search sessions based on intent characterization vectors for the respective set of search sessions comprises:
acquiring a plurality of intention core words; wherein, each intention core word is extracted from keywords related to each search behavior;
Determining, for each set of search sessions, the user intent from a plurality of the intent core words according to a degree of intent characterization vector similarity between each of the intent core words and a respective search session; the intention characterization vector similarity is used for indicating the confidence level of the intention of the corresponding user;
After the generating the user intent for each set of search sessions, further comprising:
And screening the user intention of each group of search sessions according to the confidence.
5. The promotion information presentation method according to any one of claims 1 to 3, wherein the combination of the set guidance language and the user intention, before obtaining the promotion guidance element, further comprises:
And selecting the set guide language from the candidate guide languages according to the semantic fluency between the user intention and the candidate guide languages.
6. The promotional information presentation method according to any one of claims 1-3, wherein said querying target promotional information matched with said user intent comprises:
text matching is carried out on the user intention and the title and/or the content of the candidate popularization information;
According to the text matching degree, determining seed information from the candidate popularization information;
And taking the seed information and popularization information similar to the seed information as the target popularization information.
7. A promotional information presentation apparatus, comprising:
The acquisition module is used for acquiring the intention of the user;
the query module is used for querying target popularization information matched with the user intention;
The combination module is used for combining the set guide language with the user intention to obtain a popularization guide element;
the display module is used for inserting the promotion guide element into the target promotion information for display;
The acquisition module is particularly adapted to the fact that,
Generating a directed graph according to each search behavior; the nodes in the directed graph are used for indicating keywords related to individual searching behaviors; the directional edges in the directional graph are used for connecting all nodes, and the direction of the directional edges indicates the execution sequence of all search behaviors;
generating an intention representation vector of each node in the directed graph by adopting a trained graph neural network model;
Determining the user intention according to the intention representation vector of each node in the directed graph;
The acquisition module is particularly adapted to the fact that,
Dividing each search behavior into at least one group of search sessions according to the execution time interval of each search behavior;
carrying out the weighted fusion of the intention token vectors on all nodes belonging to the same group of search sessions to obtain the intention token vector of the corresponding search session; the weight of each node is determined according to the similarity of the intention characterization vector of the corresponding node and the last node in the same group of search sessions;
the user intent for each set of search sessions is generated from the intent characterization vectors for the sets of search sessions.
8. The promotional information presentation device of claim 7, wherein the presentation module comprises:
the extraction unit is used for extracting popularization titles and popularization contents from the target popularization information;
an inserting unit for inserting the promotion guidance element between the promotion title and the promotion content;
And the display unit is used for displaying the target promotion information inserted into the promotion guide element.
9. The promotional information display apparatus according to claim 8, wherein the display module further comprises:
And the setting unit is used for setting the font format of the promotion guide element according to the font format of the promotion content.
10. The promotional information presentation device of claim 8, wherein the acquisition module is configured to,
Acquiring a plurality of intention core words; wherein, each intention core word is extracted from keywords related to each search behavior;
Determining, for each set of search sessions, the user intent from a plurality of the intent core words according to a degree of intent characterization vector similarity between each of the intent core words and a respective search session; the intention characterization vector similarity is used for indicating the confidence level of the intention of the corresponding user;
After the generating the user intent for each set of search sessions, further comprising:
And screening the user intention of each group of search sessions according to the confidence.
11. The promotional information presentation device according to any one of claims 7-9, wherein the device further comprises:
And the selection module is used for selecting the set guide language from the candidate guide languages according to the semantic fluency between the user intention and the candidate guide languages.
12. The promotional information presentation device according to any one of claims 7-9, wherein said query module is specifically configured to,
Text matching is carried out on the user intention and the title and/or the content of the candidate popularization information;
According to the text matching degree, determining seed information from the candidate popularization information;
And taking the seed information and popularization information similar to the seed information as the target popularization information.
13. An electronic device, comprising:
at least one processor; and
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 perform the promotional information presentation method of any one of claims 1-6.
14. A non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the promotional information presentation method of any one of claims 1-6.
15. A computer program product comprising a computer program which, when executed by a processor, implements the steps of the promotional information presentation method of any of claims 1-6.
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| CN114238782A (en) * | 2021-12-14 | 2022-03-25 | 北京达佳互联信息技术有限公司 | Data processing method, device, server and computer readable storage medium |
| CN114428907B (en) * | 2022-01-27 | 2024-05-28 | 北京百度网讯科技有限公司 | Information searching method, device, electronic equipment and storage medium |
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