CN111800493A - Information content pushing method and device, electronic equipment and storage medium - Google Patents
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- CN111800493A CN111800493A CN202010608395.9A CN202010608395A CN111800493A CN 111800493 A CN111800493 A CN 111800493A CN 202010608395 A CN202010608395 A CN 202010608395A CN 111800493 A CN111800493 A CN 111800493A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
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- G06F16/332—Query formulation
- G06F16/3322—Query formulation using system suggestions
- G06F16/3323—Query formulation using system suggestions using document space presentation or visualization, e.g. category, hierarchy or range presentation and selection
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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- G06F16/907—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
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- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
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Abstract
The application discloses an information content pushing method and device, electronic equipment and a storage medium, relates to the technical field of intelligent search, and can be used for intelligently recommending scenes. The specific implementation scheme is as follows: acquiring search information of a user aiming at a target field; recalling candidate information content related to the search information from a target knowledge base by using a pre-constructed knowledge graph of the target field; checking the candidate information content to obtain the information content matched with the search information in the candidate information content; and pushing the information content matched with the search information to the user. The method and the device improve the pushing effect of the information content.
Description
Technical Field
The present application relates to an intelligent search technology in the field of computer technologies, and in particular, to an information content pushing method and apparatus, an electronic device, and a storage medium.
Background
As computer technology has developed, users use search technology more and more frequently. Therefore, currently, when the search information (query) of the user is received, the related information content is often recalled directly based on the search information as the information content pushed to the user.
Disclosure of Invention
The application provides an information content pushing method and device, electronic equipment and a storage medium.
According to an aspect of the present application, there is provided an information content acquisition method, including:
acquiring search information of a user aiming at a target field;
recalling candidate information content related to the search information from a target knowledge base by using a pre-constructed knowledge graph of the target field;
checking the candidate information content to obtain the information content matched with the search information in the candidate information content;
and pushing the information content matched with the search information to the user.
According to another aspect of the present application, there is provided an information content acquiring apparatus including:
the acquisition module is used for acquiring search information of a user aiming at a target field;
the recalling module is used for recalling candidate information content related to the search information from a target knowledge base by utilizing a pre-constructed knowledge graph of the target field;
the checking module is used for checking the candidate information content to obtain the information content matched with the search information in the candidate information content;
and the pushing module is used for pushing the information content matched with the search information to the user.
According to another aspect of the present application, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the methods provided herein.
According to another aspect of the present application, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method provided herein.
According to the technology of the application, the pushing effect of the information content is improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
fig. 1 is a flowchart of an information content pushing method provided in the present application;
FIG. 2 is a schematic illustration of a product structure provided herein;
FIG. 3 is a schematic illustration of a knowledge-graph as provided herein;
FIG. 4 is a schematic diagram of a content map provided herein;
fig. 5 is a structural diagram of an information content pushing apparatus provided in the present application;
fig. 6 is a block diagram of an electronic device for implementing an information content pushing method according to an embodiment of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. 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 present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Referring to fig. 1, fig. 1 is a flowchart of an information content pushing method provided in the present application, and as shown in fig. 1, the method includes the following steps:
and step S101, acquiring search information of a user aiming at the target field.
The search information may be search information (query) transmitted by a receiving user through a terminal.
The target fields can be fields of medical cosmetology, sports, finance and the like.
And the target area may be identified by the search information.
And S102, recalling candidate information content related to the search information from a target knowledge base by using a pre-constructed knowledge graph of the target field.
In the application, different knowledge maps can be created in advance for different fields.
The target knowledge base may be one or more knowledge bases, and these knowledge bases may be knowledge bases of the target domain.
Further, the information content in the knowledge base may be advertisement content, but is not limited thereto, for example: but also news, video, etc.
In addition, the candidate information content may be a plurality of information contents that can be recalled by the search information.
Step S103, checking the candidate information content to obtain the information content matched with the search information in the candidate information content.
The checking in this step may be checking whether the recalled candidate information content matches the search information.
More accurate information content can be obtained through the verification.
And step S104, pushing the information content matched with the search information to the user.
The pushing of the information content matched with the search information to the user may be pushing the information content matched with the search information to a terminal of the user. And these information contents can be sorted at the time of pushing.
In addition, in the embodiment of the present application, pushing information content may also be understood as distributing information content.
In the application, more accurate information content can be pushed to the user through the steps, so that the pushing effect of the information content is improved.
It should be noted that the method may be applied to an intelligent recommendation scenario, which is not limited to this, for example: the method can also be applied to scenes such as intelligent search.
As an alternative embodiment, the target knowledge base includes at least two of the following items:
knowledge contents of a plurality of items in the target field, shared contents of a plurality of users in the target field, and shared contents of a plurality of organizations in the target field.
The shared content of the multiple users may be information content shared by the multiple users themselves, or information content interacted between different users, for example: the doctor asks for a question.
For example: taking the target field as the medical beauty field as an example, the target knowledge base may include knowledge contents of mainstream medical beauty items covering double-edged eyelids, weight reduction, whitening and wrinkle removal, and may also include various content types of medical beauty diaries, doctor questions and answers, institution items, and the like shared by the user. For example: as shown in fig. 2, the content library includes doctors, users (here, users refer to users of a medical beauty institution) and institutions. And can be pushed at the advertisement position to be displayed by an Aladdin card, and the Aladdin card can comprise content advertisements and content, wherein the content advertisements can be understood as paid advertisements, and the content can be understood as free advertisements. If the user clicks on the card and enters the corresponding landing page, the landing page may include a content page and associated advertisements. It should be noted that, the advertisement may be information content pushed to the user by the technical solution of the present application.
In this embodiment, since the target knowledge base includes multiple types of information contents, the diversity of the information contents pushed to the user can be improved to meet the demands of more users.
As an optional implementation, the recalling candidate information content related to search information from a target knowledge base by using a pre-constructed knowledge graph of the target domain includes:
and recalling candidate information contents related to the search information from the target knowledge base in multiple recalling modes by utilizing a pre-constructed knowledge graph of the target field.
The above-mentioned various recalling modes can include reverse retrieval based on word, vector retrieval based on vector and other recalling modes. For example: as shown in fig. 3, the inverted search may include a search of a title, an item, a paragraph tag (tag), and the like. The knowledge graph may integrate multiple knowledge bases of the target domain, such as knowledge bases of 4 industry benchmarks shown in fig. 3.
In the embodiment, the knowledge graph is used for recalling through a plurality of recalling modes, so that the recalling effect of the information content can be improved.
As an optional implementation manner, the checking the candidate information contents to obtain the information contents matching with the search information in the candidate information contents includes:
and performing relevance verification on the candidate information contents to obtain information contents matched with the search information in the candidate information contents, wherein the relevance verification is used for removing contents which are not matched with the search information in the candidate information contents.
The correlation check may also be referred to as correlation control, for example: as shown in fig. 3, correlation calculation is performed after the reverse search and the vector search to remove contents that do not match the search information from the candidate information contents.
The correlation check may be to calculate a correlation between the candidate information content and the search information, including but not limited to a correlation calculation of dimensions such as an entity, a face, and a part, so as to determine and remove information content that does not match the search information.
The correlation check may be performed on candidate information contents recalled in the multiple recall manners, that is, the correlation check is performed on information contents obtained by fusing multiple policies. As shown in fig. 3. Furthermore, the information content after the correlation check can be sequenced. The ranking may be by ranking the score of the information content or by cost, etc.
In this embodiment, since the content that does not match the search information is removed from the candidate information content by the correlation check, the accuracy of the information content is improved.
As an alternative embodiment, the knowledge-graph comprises:
a root entity corresponding to an intent of the search information and also to an intent of the information content;
the recalling candidate information content related to the search information from a target knowledge base by using the pre-constructed knowledge graph of the target field comprises the following steps:
identifying the intention of the search information, determining the root word entity corresponding to the intention of the search information according to the knowledge graph, and recalling the information content corresponding to the root word entity to obtain candidate information content related to the search information.
The knowledge graph may be obtained by capturing information content from a plurality of knowledge bases, and constructing the knowledge graph by means of tagging, rule construction, Conditional Random Field (CRF), and the like, as shown in fig. 4, the knowledge graph may include a plurality of root entities, each root entity has corresponding search information and information content, and specifically, the search information and the information content may be mounted under the related root entities by means of the intention of the search information and the intention of the information content, that is, the entities are unified, so that the root entities correspond to the intention of the search information and also correspond to the intention of the information content.
Further, as shown in fig. 4, the search information may be expanded to recall more information contents, and similarly, the information contents may be expanded to recall more information contents.
In this embodiment, since the recall is performed by the root word entity in accordance with the intention of the search information, the recall rate of the information content can be improved.
Further, in the embodiment of the present application, a provider of information content recommended to a user may also be charged, for example, an advertiser is charged. Furthermore, providers of the same or similar information contents can be selected according to identifiers of the providers (such as winfoids of advertisers), so that the information contents with high survival rate can be improved. For example: and the winfoid of the advertiser is optimized, so that the survival rate of the advertisement is improved.
In addition, the information content recommended to the user in the application can be pushed in modes of an Aladdin card, a content aggregation card, a middle page content advertisement and the like, so that the user requirements are met in an all-round mode.
In the method, search information of a user for a target field is acquired; recalling candidate information content related to the search information from a target knowledge base by using a pre-constructed knowledge graph of the target field; and checking the candidate information content to obtain the information content matched with the search information in the candidate information content. Therefore, more accurate information content can be pushed to the user, and the pushing effect of the information content is improved.
Referring to fig. 5, fig. 5 is a content pushing apparatus according to the present application, and as shown in fig. 5, the content pushing apparatus 500 includes:
an obtaining module 501, configured to obtain search information of a user for a target field;
a recalling module 502, configured to recall candidate information content related to the search information from a target knowledge base by using a pre-constructed knowledge graph of the target domain;
a checking module 503, configured to check the candidate information content to obtain an information content, which is matched with the search information, in the candidate information content;
a pushing module 504, configured to push information content matching the search information to the user.
Optionally, the recall module 502 is configured to recall candidate information content related to search information from a target knowledge base in multiple recall manners by using a pre-constructed knowledge graph of the target domain.
Optionally, the checking module 503 is configured to perform correlation checking on the candidate information contents to obtain information contents in the candidate information contents that match the search information, where the correlation checking is used to remove contents in the candidate information contents that do not match the search information.
Optionally, the knowledge-graph comprises:
a root entity corresponding to an intent of the search information and also to an intent of the information content;
the recall module 503 is configured to identify an intention of the search information, determine the root entity corresponding to the intention of the search information according to the knowledge graph, and recall information content corresponding to the root entity to obtain candidate information content related to the search information
Optionally, the target knowledge base includes at least two items:
knowledge contents of a plurality of items in the target field, shared contents of a plurality of users in the target field, and shared contents of a plurality of organizations in the target field.
The apparatus provided in this embodiment can implement each process implemented in the method embodiment shown in fig. 1, and can achieve the same beneficial effects, and is not described here again to avoid repetition.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
As shown in fig. 6, the electronic device is a block diagram of an electronic device according to an information content pushing method in 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 phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 6, the electronic apparatus includes: one or more processors 601, memory 602, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. 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 for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). In fig. 6, one processor 601 is taken as an example.
The memory 602 is a non-transitory computer readable storage medium as provided herein. The memory stores instructions executable by at least one processor to cause the at least one processor to execute the information content pushing method provided by the application. The non-transitory computer-readable storage medium of the present application stores computer instructions for causing a computer to execute the information content pushing method provided by the present application.
The memory 602 is a non-transitory computer readable storage medium, and can be used for storing non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules (for example, the obtaining module 501, the recalling module 502, the checking module 503, and the pushing module 504 shown in fig. 5) corresponding to the information content pushing method in the embodiment of the present application. The processor 601 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 602, that is, implements the information content pushing method in the above method embodiment.
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 data created according to use of the electronic device of the information content push method, and the like. Further, the memory 602 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 602 optionally includes a memory remotely located from the processor 601, and these remote memories may be connected to the electronic device of the information content push method through 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 of the information content pushing method may further include: an input device 603 and an output device 604. The processor 601, the memory 602, the input device 603 and the output device 604 may be connected by a bus or other means, and fig. 6 illustrates the connection by a bus as an example.
The input device 603 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device of the information content push method, such as an input device of a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointing stick, one or more mouse buttons, a track ball, a joystick, etc. The output devices 604 may include a display device, auxiliary lighting devices (e.g., LEDs), and tactile feedback devices (e.g., vibrating motors), among others. 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 can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. 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 a pointing device (e.g., a mouse or a 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 can 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, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end 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 back-end, 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 clients and servers. A client and server are generally 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.
According to the technical scheme of the embodiment of the application, search information of a user for a target field is acquired; recalling candidate information content related to the search information from a target knowledge base by using a pre-constructed knowledge graph of the target field; and checking the candidate information content to obtain the information content matched with the search information in the candidate information content. Therefore, more accurate information content can be pushed to the user, and the pushing effect of the information content is improved.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (12)
1. An information content pushing method, comprising:
acquiring search information of a user aiming at a target field;
recalling candidate information content related to the search information from a target knowledge base by using a pre-constructed knowledge graph of the target field;
checking the candidate information content to obtain the information content matched with the search information in the candidate information content;
and pushing the information content matched with the search information to the user.
2. The method of claim 1, wherein the recalling candidate information content related to search information from a target knowledge base by using a pre-constructed knowledge graph of the target domain comprises:
and recalling candidate information contents related to the search information from the target knowledge base in multiple recalling modes by utilizing a pre-constructed knowledge graph of the target field.
3. The method of claim 1, wherein said checking the candidate information contents to obtain the information contents of the candidate information contents matching the search information comprises:
and performing relevance verification on the candidate information contents to obtain information contents matched with the search information in the candidate information contents, wherein the relevance verification is used for removing contents which are not matched with the search information in the candidate information contents.
4. The method of claim 1, wherein the knowledge-graph comprises:
a root entity corresponding to an intent of the search information and also to an intent of the information content;
the recalling candidate information content related to the search information from a target knowledge base by using the pre-constructed knowledge graph of the target field comprises the following steps:
identifying the intention of the search information, determining the root word entity corresponding to the intention of the search information according to the knowledge graph, and recalling the information content corresponding to the root word entity to obtain candidate information content related to the search information.
5. The method of claim 1, wherein the target-aware library comprises at least two of:
knowledge contents of a plurality of items in the target field, shared contents of a plurality of users in the target field, and shared contents of a plurality of organizations in the target field.
6. An information content pushing apparatus comprising:
the acquisition module is used for acquiring search information of a user aiming at a target field;
the recalling module is used for recalling candidate information content related to the search information from a target knowledge base by utilizing a pre-constructed knowledge graph of the target field;
the checking module is used for checking the candidate information content to obtain the information content matched with the search information in the candidate information content;
and the pushing module is used for pushing the information content matched with the search information to the user.
7. The apparatus of claim 6, wherein the recall module is configured to recall candidate information content related to search information from a target knowledge base in a plurality of recall manners by using a pre-constructed knowledge graph of the target domain.
8. The apparatus of claim 6, wherein the checking module is configured to perform a correlation check on the candidate information contents to obtain information contents of the candidate information contents that match the search information, wherein the correlation check is configured to remove contents of the candidate information contents that do not match the search information.
9. The apparatus of claim 6, wherein the knowledge-graph comprises:
a root entity corresponding to an intent of the search information and also to an intent of the information content;
the recalling module is used for identifying the intention of the search information, determining the root word entity corresponding to the intention of the search information according to the knowledge graph, and recalling the information content corresponding to the root word entity so as to obtain the candidate information content related to the search information.
10. The apparatus of claim 6, wherein the target-aware library comprises at least two of:
knowledge contents of a plurality of items in the target field, shared contents of a plurality of users in the target field, and shared contents of a plurality of organizations in the target field.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
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| CN112954025A (en) * | 2021-01-29 | 2021-06-11 | 北京百度网讯科技有限公司 | Information pushing method, device, equipment and medium based on layered knowledge graph |
| CN112989190A (en) * | 2021-03-09 | 2021-06-18 | 北京百度网讯科技有限公司 | Commodity mounting method and device, electronic equipment and storage medium |
| CN113254824A (en) * | 2021-05-14 | 2021-08-13 | 北京百度网讯科技有限公司 | Content determination method, apparatus, medium, and program product |
| CN113468425A (en) * | 2021-06-30 | 2021-10-01 | 北京百度网讯科技有限公司 | Knowledge content distribution method and device, electronic equipment and storage medium |
| CN114168756A (en) * | 2022-01-29 | 2022-03-11 | 浙江口碑网络技术有限公司 | Query understanding method and apparatus for search intention, storage medium, and electronic device |
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