WO2022048360A1 - 一种搜索结果展示的方法、装置及计算机存储介质 - Google Patents

一种搜索结果展示的方法、装置及计算机存储介质 Download PDF

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Publication number
WO2022048360A1
WO2022048360A1 PCT/CN2021/109325 CN2021109325W WO2022048360A1 WO 2022048360 A1 WO2022048360 A1 WO 2022048360A1 CN 2021109325 W CN2021109325 W CN 2021109325W WO 2022048360 A1 WO2022048360 A1 WO 2022048360A1
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Prior art keywords
entity
target
information
search request
identification information
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English (en)
French (fr)
Inventor
汪忠超
乔超
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Beijing ByteDance Network Technology Co Ltd
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Beijing ByteDance Network Technology Co Ltd
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Priority to US18/008,105 priority Critical patent/US20230315736A1/en
Publication of WO2022048360A1 publication Critical patent/WO2022048360A1/zh
Anticipated expiration legal-status Critical
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    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/40Information retrieval; Database structures therefor; File system structures therefor of multimedia data, e.g. slideshows comprising image and additional audio data
    • G06F16/43Querying
    • G06F16/435Filtering based on additional data, e.g. user or group profiles
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28Databases characterised by their database models, e.g. relational or object models
    • G06F16/284Relational databases
    • G06F16/288Entity relationship models
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/242Query formulation
    • G06F16/2433Query languages
    • G06F16/244Grouping and aggregation
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/245Query processing
    • G06F16/2455Query execution
    • G06F16/24553Query execution of query operations
    • G06F16/24554Unary operations; Data partitioning operations
    • G06F16/24556Aggregation; Duplicate elimination
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24Querying
    • G06F16/248Presentation of query results
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/953Querying, e.g. by the use of web search engines
    • G06F16/9535Search customisation based on user profiles and personalisation
    • GPHYSICS
    • G06COMPUTING OR CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/953Querying, e.g. by the use of web search engines
    • G06F16/9538Presentation of query results

Definitions

  • the present disclosure relates to the field of Internet technologies, and in particular, to a method, an apparatus, and a computer storage medium for displaying search results.
  • Embodiments of the present disclosure at least provide a method, an apparatus, and a computer storage medium for displaying search results.
  • an embodiment of the present disclosure provides a method for displaying search results, the method comprising:
  • a search request is sent; the search request corresponds to multiple entities;
  • the multi-entity aggregation result includes entity information of multiple target entities matching the search request; the entity information is based on the association corresponding to the search request access to media content;
  • the multi-entity aggregation results are displayed.
  • the entity information includes identification information of the target entity and target content information associated with the target entity;
  • the target content information associated with the target entity includes: among the multiple associated media contents corresponding to the search request, at least one associated media content corresponding to the target entity.
  • displaying the multi-entity aggregation result includes:
  • the content information associated with the target recommendation entity is displayed in other display areas.
  • the identification information of the multiple target entities is displayed in the first display area, including:
  • the identification information of the multiple target entities is displayed in sequence in the first display area.
  • displaying the multi-entity aggregation result includes:
  • At least one associated media content corresponding to the target recommendation entity is displayed in sequence in the second display area.
  • the determining the target recommendation entity corresponding to the selected target identification information in the identification information of the multiple target entities includes:
  • the target entity displayed in the first display position of the first display area is used as the initial target recommendation entity;
  • the other target entities are used as the updated target recommendation entities.
  • the target content information associated with the target entity further includes: encyclopedic knowledge information and/or recommendation information of the target entity.
  • displaying the multi-entity aggregation result includes:
  • the encyclopedic knowledge information and/or recommendation information of the target recommendation entity is displayed in the third display area.
  • the target content information associated with the target entity further includes: function entry information of the target recommendation entity; the function entry information is used to trigger the display of a consumption page corresponding to the target recommendation entity.
  • displaying the multi-entity aggregation result includes:
  • the consumption page corresponding to the target recommendation entity is displayed.
  • the function entry information of the target recommendation entity is displayed in the fourth display area, including:
  • the function entry information of the target recommended entity is displayed in the fourth display area.
  • an embodiment of the present disclosure further provides a method for displaying search results, the method comprising:
  • a multi-entity aggregated result corresponding to the search request is generated.
  • the entity information includes identification information of the target entity and target content information associated with the target entity;
  • the target content information associated with the target entity includes: among the multiple associated media contents corresponding to the search request, at least one associated media content corresponding to the target entity.
  • the method further includes:
  • the determining the entity information of the target entity according to the associated media content includes:
  • the entity information of the target entity is determined.
  • the entity information of the target entity is determined, including:
  • the identification information of the target entity is selected from the identification information of the found core entity.
  • the attribute information of the found core entity is determined based on the knowledge graph information corresponding to the identification information of the core entity and the associated media content, including:
  • the attribute features of the associated media content include: the attribute information of the author, the degree of correlation between the associated media content and the search request, and at least one of the order positions of the associated media content in this search. A sort of.
  • the entity extraction is performed on multiple media contents in advance to obtain the identification information of the extracted multiple core entities, including:
  • Entity extraction is performed on the multiple media contents based on the pre-trained entity extraction model to obtain the identification information of the extracted multiple core entities; the entity extraction model is obtained by training the media content samples based on the identification information of the core entities manually marked of.
  • the attribute-based search request refers to a search request that uses multiple attribute keywords to characterize search intent
  • the obtaining and the search request Matched associated media content including:
  • the determining the identification information of the target entity and the content information associated with the target entity according to the associated media content includes:
  • the identification information of the target entity and the content information associated with the target entity for displaying in the multi-entity aggregation result are extracted.
  • the target content information associated with the target entity further includes: encyclopedic knowledge content and/or recommendation information;
  • the encyclopedic knowledge content and/or recommendation information is determined according to the following steps:
  • the recommendation information corresponding to the target entity is determined.
  • an embodiment of the present disclosure further provides an apparatus for displaying search results, including:
  • a sending module configured to send a search request in response to a search trigger instruction; the search request corresponds to multiple entities;
  • a first obtaining module configured to obtain a multi-entity aggregation result corresponding to the search request; wherein the multi-entity aggregation result includes entity information of multiple target entities matching the search request; the entity information is based on The associated media content corresponding to the search request is obtained;
  • a display module configured to display the multi-entity aggregation result.
  • the entity information includes identification information of the target entity and target content information associated with the target entity; wherein the target content information associated with the target entity includes: Among the plurality of associated media contents, at least one associated media content corresponding to the target entity is included.
  • the display module is specifically configured to display the identification information of the multiple target entities in the first display area; determine the selected target identification information in the identification information of the multiple target entities The corresponding target recommendation entity; the content information associated with the target recommendation entity is displayed in other display areas.
  • the display module is further specifically configured to sequentially display the identification information of the multiple target entities in the first display area according to the acquired identification information of the multiple target entities.
  • the display area is further specifically configured to sequentially display at least one associated media content corresponding to the target recommendation entity in the second display area.
  • the display module is further configured to, after acquiring the multi-entity aggregation result, use the target entity displayed in the first display position of the first display area as the initial target recommendation entity;
  • the other target entities are used as the updated target recommendation entities.
  • the target content information associated with the target entity further includes: encyclopedic knowledge information and/or recommendation information of the target entity.
  • the display module is further specifically configured to display the encyclopedic knowledge information and/or recommendation information of the target recommendation entity in a third display area.
  • the target content information associated with the target entity further includes: function entry information of the target recommendation entity; the function entry information is used to trigger the display of a consumption page corresponding to the target recommendation entity.
  • the display module is further specifically configured to display the function entry information of the target recommended entity in the fourth display area; after detecting a triggering operation for the function entry information, display the function entry information.
  • the display module is further specifically configured to display the function entry information of the target recommended entity in the fourth display area when the entity category of the target recommended entity belongs to the target entity category .
  • an embodiment of the present disclosure further provides an apparatus for displaying search results, including:
  • the receiving module is configured to receive a search request, where the search request corresponds to multiple entities.
  • a second acquiring module configured to acquire associated media content matching the search request.
  • a determining module configured to determine entity information of multiple target entities according to the associated media content.
  • a generating module configured to generate a multi-entity aggregation result corresponding to the search request based on the entity information of the multiple target entities.
  • the entity information includes identification information of the target entity and target content information associated with the target entity;
  • the target content information associated with the target entity includes: among the multiple associated media contents corresponding to the search request, at least one associated media content corresponding to the target entity.
  • the apparatus further includes an entity extraction module, configured to perform entity extraction on multiple media contents in advance, obtain identification information of the extracted multiple core entities, and store the identification information of each media content Correspondence with the extracted identification information of the core entity;
  • the determining module is specifically configured to determine the entity information of the target entity according to the identification information of the associated media content and the stored corresponding relationship.
  • the determining module is further specifically configured to search for the identification information of the core entity corresponding to the associated media content according to the identification information of the associated media content and the stored correspondence ; Based on the knowledge graph information corresponding to the identification information of the core entity and the associated media content, determine the attribute information of the found core entity; Based on the intent classification information corresponding to the search request, and the attributes of the core entity information, and select the identification information of the target entity from the identification information of the found core entity.
  • the determining module is further specifically configured to search the classification information corresponding to the identification information of the core entity from the knowledge graph;
  • the attribute characteristics of the content and the number of times the core entity appears in different associated media contents are used as the attribute information of the core entity; wherein, the attribute characteristics of the associated media content include: the attribute information of the author, the associated media content and At least one of the degree of correlation between the search requests and the arrangement order of the associated media content in this search.
  • the entity extraction module is specifically configured to perform entity extraction on the multiple media contents based on a pre-trained entity extraction model, and obtain identification information of the extracted multiple core entities; the entity extraction The extraction model is trained based on the media content samples manually marked with the identification information of the core entities.
  • the search request is an attribute-based search request
  • the attribute-based search request refers to a search request that uses multiple attribute keywords to represent search intent
  • the second obtaining module specifically for obtaining knowledge graph content matching the attribute keywords in the search request
  • the determining module is further specifically configured to extract, from the knowledge graph content matching the attribute keywords in the search request, the identification information of the target entity that is displayed in the multi-entity aggregation result and the information about the target entity. Describe the content information associated with the target entity.
  • the target content information associated with the target entity further includes: encyclopedic knowledge content and/or recommendation information;
  • the apparatus further includes a target content information determination module, configured to obtain encyclopedic knowledge content matching the identification information of the target entity based on the identification information of the target entity; and/or, based on each association corresponding to the target entity User behavior data and/or author attribute information of the media content to determine recommendation information corresponding to the target entity.
  • a target content information determination module configured to obtain encyclopedic knowledge content matching the identification information of the target entity based on the identification information of the target entity; and/or, based on each association corresponding to the target entity User behavior data and/or author attribute information of the media content to determine recommendation information corresponding to the target entity.
  • embodiments of the present disclosure further provide a computer device, including: a processor, a memory, and a bus, where the memory stores machine-readable instructions executable by the processor, and when the computer device runs, the processing A bus communicates between the processor and the memory, and when the machine-readable instructions are executed by the processor, the above-mentioned first aspect, or the steps in any possible implementation manner of the first aspect, or the above-mentioned first aspect is executed.
  • an embodiment of the present disclosure further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and the computer program is executed by a processor to execute the first aspect, or any one of the first aspect. Steps in one possible implementation manner, or perform the above-mentioned second aspect, or steps in any possible implementation manner of the second aspect.
  • a multi-entity aggregated result corresponding to the search request can be obtained, and the multi-entity aggregated result includes the Request the entity information of multiple target entities that match the search request.
  • the client can intuitively display the entity information of multiple target entities that match the search request to the user, and the user can intuitively see the multiple target entities through the aggregated results, which is convenient
  • the user further filters the interested target entities, which improves the efficiency of information search and saves the search time.
  • FIG. 1 shows a flowchart of a method for displaying search results provided by an embodiment of the present disclosure
  • FIG. 2 shows a schematic diagram of a display interface of a first display area provided by an embodiment of the present disclosure
  • FIG. 3 shows a schematic diagram of a display interface of a search result provided by an embodiment of the present disclosure
  • FIG. 4 shows a schematic diagram of another display interface of a search result provided by an embodiment of the present disclosure
  • FIG. 5 shows a schematic diagram of a display interface of a detail page of associated media content provided by an embodiment of the present disclosure
  • FIG. 6 shows a schematic diagram of a display interface of a consumption page corresponding to a target recommendation entity provided by an embodiment of the present disclosure
  • FIG. 7 shows a schematic diagram of a display interface of another consumption page corresponding to a target recommendation entity provided by an embodiment of the present disclosure
  • FIG. 8 shows a flowchart of another method for displaying search results provided by an embodiment of the present disclosure
  • FIG. 9 shows a schematic diagram of an apparatus for displaying search results provided by an embodiment of the present disclosure.
  • FIG. 10 shows a schematic diagram of another apparatus for displaying search results provided by an embodiment of the present disclosure.
  • FIG. 11 shows a schematic diagram of a computer device provided by an embodiment of the present disclosure
  • FIG. 12 shows a schematic diagram of another computer device provided by an embodiment of the present disclosure.
  • the embodiments of the present disclosure provide a method, a device, and a computer storage medium for displaying search results.
  • the server When a user initiates a search request on a client, the server will aggregate entity information of multiple target entities that meet the user's search request. Together, the multi-entity aggregation result is generated, and the multi-entity aggregation result is sent to the client, and the client displays the above multi-entity aggregation result.
  • the user can see multiple target entities at once through the multi-entity aggregation result, which is convenient
  • the user can quickly locate the interested target entity, which improves the efficiency of information search and saves the search time.
  • the multi-entity aggregation result may include identification information of each target entity and target content information associated with each target entity, and the user terminal may display the identification information of multiple recommended entities that match the search request.
  • the execution subject of the method for displaying search results provided by this embodiment of the present disclosure is generally a computer with certain computing capabilities equipment, the computer equipment includes, for example: terminal equipment or server or other processing equipment, the terminal equipment may be user equipment (User Equipment)
  • the method of displaying the search results may be implemented by the processor invoking computer-readable instructions stored in the memory.
  • the user terminal may be an electronic device with a display function such as a terminal device, a tablet computer, a computer device, etc.; wherein, the terminal device may be a user equipment (User Equipment, UE), a mobile device, a user terminal, a terminal, a cordless phone, a personal digital Processing (Personal Digital Assistant, PDA), handheld devices, computing devices, in-vehicle devices, etc.
  • UE User Equipment
  • PDA Personal Digital Assistant
  • FIG. 1 is a flowchart of a method for displaying search results provided by an embodiment of the present disclosure
  • the method includes steps S101-S103, wherein:
  • the search trigger instruction may be initiated by the user performing a click operation on the search button on the search page.
  • the search request carries the search content input by the user, which may represent the search intention of the user.
  • the search request processed by the embodiment of the present disclosure involves multiple entities. For example, when a user searches for "movies suitable for couples to watch", the search request corresponds to multiple movie entities.
  • the client sends the user's search request to the server.
  • the server can obtain the associated media content that matches the search request, and determine the entity information of multiple target entities according to the associated media content, and based on the multiple target entities the entity information, generate a multi-entity aggregation result corresponding to the search request, and return the multi-entity aggregation result to the user side.
  • the server-side embodiment see the description of the server-side embodiment.
  • the multi-entity aggregation result obtained by the user terminal includes entity information of multiple target entities matching the search request, and the entity information is obtained based on the associated media content corresponding to the search request.
  • the entity information may include identification information of the target entity and target content information associated with the target entity.
  • the identification information of the target entity may include an entity identification number, an entity name, and a thumbnail image representing the target entity, and may also include a label of the order position of the target entity in the multiple target entities included in the multi-entity aggregation result, etc.;
  • the thumbnail of the entity can be a promotional picture, an introduction picture, etc.;
  • the target content information associated with the target entity may include: among the plurality of associated media contents corresponding to the search request, at least one associated media content corresponding to the target entity obtained is obtained, that is, the embodiment of the present disclosure may display a plurality of associated media contents.
  • the associated media content corresponding to the user's search request can also be displayed synchronously.
  • the target content information associated with the target entity may also include: encyclopedic knowledge information and/or recommendation information of the target entity, and/or function entry information corresponding to the target entity;
  • the function entry information can be used to instruct the user to click to enter the details page of the target entity.
  • the details page can be the specific display interface of the target entity, or The purchase page corresponding to the target entity.
  • the above-mentioned encyclopedia knowledge information and/or recommendation information, and/or the above-mentioned function entry information can be selectively displayed.
  • Entity categories include, for example, film and television, commodities, popular science, music, recipes, etc.
  • function entry information can be displayed.
  • the identification information of the multiple target entities may be displayed in sequence in the first display area of the user terminal.
  • the identification information may include entity names, thumbnail images representing the entities, and arrangement order bits of each entity in the multi-entity aggregation result.
  • the user terminal when the user enters the search content on the screen of the user terminal as "movies suitable for couples to watch at night", the multi-entity aggregated results received by the user terminal involve the film and television works "Love in June Flowers”, “Rejuvenation”, “Love in Love” Notebook” and “The Beautiful Legend of Sicily” are multiple target entities. According to the arrangement order of multiple target entities, the user terminal sequentially displays the name and thumbnail of "Love June Flowers", the name and thumbnail of "Rejuvenation”, and the name and thumbnail of "Love Notebook” in the first display area.
  • the target recommended entity corresponding to the selected target identification information in the identification information of the multiple target entities is determined, and the target is displayed in other display areas. Recommends the content information associated with the entity.
  • the user can quickly locate and display multiple target entities displayed in the first display area.
  • the user terminal can display the content information associated with the target recommendation entity selected by the user in other display areas after confirming the target recommendation entity that the user is interested in.
  • the first display area in the first display area can be displayed.
  • the target entity of the placement is used as the default initial target recommendation entity.
  • the target recommendation entity is the target entity arranged in the first display position among the multiple target entities
  • the content information associated with the target recommendation entity arranged in the first display position is displayed in other display areas.
  • the user terminal detects the selection operation of the identification information of other target entities displayed in other display positions in the first display area
  • the other target entities are regarded as the updated target recommendation entities
  • the updated target entities are displayed in other display areas. Recommends the content information associated with the entity.
  • the content information associated with the target recommendation entity may include at least one associated media content corresponding to the target recommendation entity, encyclopedia knowledge information and/or recommendation information of the target recommendation entity, and function entry information corresponding to the target entity.
  • the recommendation information may include a text introduction, graphic introduction, video or audio introduction of the target recommended entity, and the encyclopedic knowledge information is the encyclopedic knowledge content that introduces the target recommended entity.
  • the at least one associated media content corresponding to the target recommended entity may be displayed in the second display area according to the arrangement order of the at least one associated media content corresponding to the target recommended entity.
  • the encyclopedic knowledge information and/or recommendation information of the target recommendation entity may be displayed in the third display area.
  • the content information associated with the target recommended entity also includes function entry information, and the function entry information of the target recommended entity can be displayed in the fourth display area.
  • the process of displaying the multi-entity aggregation result by the user terminal is as follows: the entity name of each target entity included in the multi-entity aggregation result and the thumbnail image corresponding to each target entity are placed in the order of the arrangement of each target entity. It is displayed in the first display area, and at the same time, the target entity displayed in the first display position of the first display area is used as the initial target recommendation entity, and the target content information associated with the initial target recommendation entity is displayed in other display areas.
  • the target entity selected by the user is used as the new target recommendation entity, and the target content information associated with the new target recommendation entity is displayed in other display areas;
  • the second display area at least one related media content corresponding to the target recommendation entity is displayed in the order of the related media content and the screen size of the user terminal;
  • the third display area the encyclopedia knowledge information of the target recommended entity is displayed. and/or recommendation information; if the entity category of the target recommendation entity belongs to the target entity category, the function entry information of the target recommendation entity is displayed in the fourth display area.
  • the content information associated with the target recommended entity may not include function entry information, that is, there may not be a fourth display area.
  • the server determines, according to the user's search request, that multiple target entities that meet the user's search request are film and television works respectively: “June Flower”, “Rejuvenation”, “Love Notebook”, “The Beautiful Legend of Sicily”, and the corresponding entity categories of the above-mentioned multiple target entities belong to the above-mentioned target entity category, and the server generates multiple entities based on the above-mentioned multiple target entities Aggregate the result, and return the multi-entity aggregation result to the user terminal.
  • the user terminal Based on the identification information of multiple target entities in the multi-entity aggregation result, the user terminal sequentially displays "Love June Flowers", “Rejuvenation”, The entity names, entity thumbnails and the labels of the arrangement order positions of "Love Notebook” and “The Beautiful Legend of Sicily”; when the user does not select the identification information of any target entity among the multiple target entities displayed in the first display area, Take “Love June Flower” as the default initial target recommendation entity, and display related media content such as article introduction content, film and television comment content, and highlight content related to "Love June Flower” in the second display area;
  • the third display area displays the brief introduction content of the film and television corresponding to "Love June Flower” and the instruction information "View Encyclopedia Information” that instructs the user to view the encyclopedic knowledge of the film and television work (here, after the user clicks "View Encyclopedia Information", you can jump to Go to the encyclopedia knowledge details page corresponding to the film and television work), and display the function entry information indicating the user's operation in the fourth display area (here
  • the server determines, according to the user's search request, that multiple target entities that meet the user's search request are film and television works respectively: “June Flower”, “Rejuvenation”, “Love Notebook”, “The Beautiful Legend of Sicily”, and the corresponding entity categories of the above multiple target entities belong to the target entity category, the server generates a multi-entity aggregation result based on the above multiple target entities, and The multi-entity aggregation result is returned to the client, and the client, based on the identification information of multiple target entities in the multi-entity aggregation result, displays "Love June Flowers", “Rejuvenation” and “Love Notebook” in sequence in the first display area.
  • a multi-entity aggregated result corresponding to the search request can be obtained, and the multi-entity aggregated result includes multiple entities matching the search request.
  • the entity information of the target entity the user terminal can intuitively display the entity information of multiple target entities that match the search request to the user, and the user can intuitively see multiple target entities through the aggregated results, which facilitates the user to further filter the interested entities. It improves the efficiency of information search and saves search time.
  • the method further includes: displaying any associated media content in response to a selection operation for any associated media content details page.
  • the user after the user selects the associated media content of the target recommendation entity displayed on the screen, the user jumps to the details page of the associated media content, and displays the details page of the associated media content on the client screen.
  • the user terminal receives a multi-entity aggregation result, based on the identification of multiple target entities in the multi-entity aggregation result.
  • the entity names, entity thumbnails and the labels of the arrangement order position of "Love June Flower”, “Rejuvenation”, “Love Notebook” and “The Beautiful Legend of Sicily” are displayed in sequence;
  • "Love June Flowers” will display in the second display area the introduction information of the film and television commentary content related to "Love June Flowers”, as well as the related media content such as the introduction information of the highlight content, in the third display area Display the encyclopedic knowledge information corresponding to "Love June Flowers", and display the function entry information indicating the user's operation in the fourth display area.
  • the detailed page of the film and television review content is displayed on the user terminal screen.
  • the specific details page may be the interface display diagram shown in FIG. 5 , taking the user terminal as a mobile phone as an example.
  • the method further includes: after detecting a trigger operation for the function entry information, responding to the function entry The information triggering operation displays the consumption page corresponding to the target recommendation entity.
  • the trigger operation may be a double-click operation, a single-click operation, or other selected operations.
  • the consumption page may be a play or purchase page, or a specific play or display detail page of the recommended entity.
  • the user selects the function entry information of the target recommended entity displayed on the screen, it jumps to the consumption page of the associated media content, and displays the consumption page corresponding to the target recommended entity on the user terminal screen.
  • the user terminal after the user terminal initiates a search request corresponding to multiple entities, it obtains multi-entity aggregation results, and displays multiple target entities "Love June Flowers”, “Rejuvenation”, “Love Notebook”, The entity name, entity thumbnail, and sequence number of "The Beautiful Legend of Sicily”; when the user selects the identification information of "Rejuvenation” among the multiple target entities displayed in the first display area, "Rejuvenation” is recommended as a target Entity, in the second display area, display the content of film and television reviews related to "Rejuvenation", as well as related media content such as highlight content, display the encyclopedia knowledge information corresponding to "Rejuvenation” in the third display area, and instruct the user in the fourth display area. Function entry information for the operation.
  • the specific consumption page can be the interface display diagram shown in FIG.
  • the specific consumption page may be the interface display diagram shown in FIG. 7 , taking the user terminal as a mobile phone as an example.
  • a flowchart of a method for displaying search results provided by an embodiment of the present disclosure can be applied to a server, and the method includes steps S801 to S804, wherein:
  • search request corresponds to multiple entities.
  • the associated media content may be one or more media contents; the associated media content may be a text document, a mixed image and text document, a picture, a video, an audio, and the like.
  • the request type of the search request may include attribute class and entity collection class.
  • search request is an attribute search request
  • knowledge graph content matching the attribute keywords in the search request may be acquired according to multiple attribute keywords included in the search request.
  • the attribute-based search request refers to a search request that uses multiple attribute keywords to represent search intent. For example: when the search content entered by the user on the search page is "post-90s female star with a height of 170cm", the multiple attribute keywords "post-90s", “height”, “170cm” and “female star” represent the user's search intent.
  • the knowledge graph can be a semantic network composed of multiple nodes and connecting edges between nodes.
  • a node can represent an entity
  • the information of the node is the relevant information of the corresponding entity
  • the connecting edge between nodes can represent the entity.
  • Various semantic relationships between them such as parental relationship, husband and wife relationship, agent, friend, etc.
  • the client sends the search request to the server, and the server receives the above search request and determines.
  • the type of the search request is an attribute type search request, and the multiple attribute keywords contained in the search content corresponding to the search request are extracted as "post-90s", “height”, “170cm”, and "female star”.
  • the multiple attributes Keywords obtain the related media content matching the above gender, age, and height attributes in the knowledge graph, and feed back the found related media content to the user.
  • a plurality of associated media contents matching the search request can be determined by the following method, which is specifically described as follows: in the case that the query intent corresponding to the search request is an objective type The associated media content of the objective answer; if the query intent corresponding to the search request is a subjective type of intent, search for the associated media content with a subjective type of search result matching the search request.
  • the query intent type corresponding to the search request may include objective intent and subjective intent.
  • the recalled is the related media content containing objective answers
  • the search request of subjective type of intent the recalled is the related media content of the published related subjective type of opinion content.
  • standard semantic extraction can be used to obtain standard sentences corresponding to the search requests, and further search for associated media content matching the obtained standard sentences.
  • a standard sentence corresponding to the search sentence in the search request may be determined based on a pre-trained generalization model; and then, based on the standard sentence, associated media content matching the search request is acquired.
  • the generalization model here is trained based on a large number of search sentence samples marked with standard sentences.
  • the generalization model can first extract keywords from the search sentences, and then convert the extracted keywords into standard sentences.
  • the generalization model pre-trained in the server will respond to the above search content "What are the four famous books” or “What are the four famous books?” Keyword extraction is performed on “What are the Four Great Classics”, the search keyword “Four Great Classics” corresponding to the above search content is extracted, and a standard sentence "What are the Four Great Classics" is formed.
  • the server After receiving the search request from the user, the server inputs the search content corresponding to the search request into the generalization model, determines the standard sentence corresponding to the search request, and queries the media content library based on the standard sentence, and determines the corresponding standard sentence. Multiple associated media contents corresponding to the search request.
  • the search content input by the user in the search interface is: “what are the four famous works", when the user clicks the "search” button, the server inputs the above search content "what are the four famous works” into the generalization model, It is determined that the standard sentence corresponding to the above search content is "what are the four famous novels", and based on the standard sentence, the media content library is queried for related media content that matches the search content.
  • step S803 after obtaining the associated media content matching the search request based on step S802, the entity information of multiple target entities matching the search request may be determined through step S803, which is specifically described as follows.
  • the entity information may include identification information of the target entity, target content information associated with the target entity, and the like.
  • the identification information of the target entity may include an entity identification number, an entity name, and a thumbnail image representing the target entity, and may also include a label of the order position of the target entity in the multiple target entities included in the multi-entity aggregation result, etc.;
  • the thumbnail of the entity can be a promotional picture, an introduction picture, etc.;
  • the target content information associated with the target entity may include: among the multiple associated media contents corresponding to the search request, at least one obtained associated media content corresponding to the target entity, encyclopedic knowledge information and/or recommendation information of the target entity , and the function entry information corresponding to the target entity; wherein, the recommendation information can be the text introduction content, graphic introduction content, video or audio introduction content, etc. of the target entity; the function entry information can be used to instruct the user to click to enter the target entity.
  • the detail page of the entity. The detail page can be the specific display interface of the target entity or the purchase page corresponding to the target entity.
  • the server performs entity extraction on multiple media contents in advance, obtains the identification information of the extracted multiple core entities, and stores the corresponding relationship between the identification information of each media content and the extracted identification information of the core entities;
  • the identification information of the core entity may include information such as entity name, entity thumbnail, and entity identification number; the identification information of the media content may include title information of the media content, access address of the media content, and the like.
  • entity extraction can be performed on the plurality of media contents based on a pre-trained entity extraction model to obtain the identification information of the extracted multiple core entities; wherein, the entity extraction model is the media content based on the identification information of the manually marked core entities sample training.
  • the server obtains the identification information of the associated media content according to step S802, and the corresponding relationship between the stored identification information of each associated media content and the extracted identification information of the core entity, and searches for the identification information associated with each associated media content.
  • identification information of the corresponding core entity and based on the knowledge graph information and associated media content corresponding to the identification information of the core entity, determine the attribute information of the found core entity; and based on the intent classification information corresponding to the search request, and the The attribute information of the core entity, and the identification information of the target entity is selected from the identification information of the found core entity.
  • the attribute information of the found core entity can be determined by the following methods, and the specific description is as follows: searching for the classification information corresponding to the identification information of the core entity from the knowledge graph; The attribute characteristics of the associated media content, and the number of times the core entity appears in different associated media contents, etc., are used as the attribute information of the core entity;
  • the attribute features of the associated media content include: the attribute information of the author, the degree of correlation between the associated media content and the search request, and at least one of the order positions of the associated media content in this search. A sort of.
  • the knowledge graph stores the identification information of each entity and the classification information of each entity.
  • the classification information can represent the types of candidate entities, which can include literature, books, movies, art, life, transportation, automobiles, society, brands, food, commodities, popular science, music, recipes, etc.
  • the attribute information of the author corresponding to the associated media content may include author authority, author influence, etc.; the correlation between the associated media content and the search request is used to indicate whether the associated media content meets the user's search needs.
  • the server acquires the identifiers of multiple core entities according to the identifier information of the associated media content obtained in step S802 and the corresponding relationship between the stored identifier information of each associated media content and the extracted identifier information of the core entity information; based on the identification information of each core entity above, look up the knowledge graph, determine the classification information of each core entity, based on the above classification information and the attribute information of the author of the associated media content corresponding to each core entity, each core entity The degree of correlation between the corresponding associated media content and the search request, and the arrangement order of the associated media content corresponding to each core entity in this search, in the identification information of the plurality of core entities obtained above, determine Identification information of the target entity.
  • the encyclopedic knowledge content and/or recommendation information in the target content information associated with the target entity can be determined by the following method, which is specifically described as follows: Based on the identification information of the target entity, obtain Encyclopedia knowledge content matching the identification information of the target entity; and/or, based on user behavior data and/or author attribute information of each associated media content corresponding to the target entity, determine recommendation information corresponding to the target entity.
  • the encyclopedic knowledge content including the entity name and entity identification number information of the target entity can be obtained in the media content library.
  • the user behavior data may include the user's comment content, search content, etc. after browsing the associated media content;
  • the author attribute information may include author identification information, author authority, author influence, and the like.
  • semantic analysis can be performed on the comment content and search content after the user browses the associated media content corresponding to each target entity, to determine the associated media content that the user is interested in, and use the associated media content that the user is interested in as the recommendation information of the target entity. It can also be based on the author identification information, author authority, and author influence of each associated media content corresponding to each target entity, among the authors of each associated media content corresponding to each target entity, it is determined that the author authority is greater than the predicted value. A target author whose authoritative threshold and/or author influence is greater than the preset influence threshold is set, in the media content library, the associated media content corresponding to the target author's identification information is used as the recommendation information of the target entity.
  • the author identification information can also be based on the author identification information, author influence, author authority of each associated media content corresponding to each target entity, and the comment content and search content after the user browses each associated media content corresponding to each target entity.
  • the author's authority is greater than the preset authority threshold and/or the author's influence is greater than the preset influence threshold.
  • the identification information and related media content that the user is interested in is used as the recommendation information for the target entity.
  • the entity information of the target entity may be determined whether the entity information of the target entity contains function entry information based on the entity category of the target entity, which is specifically described as follows: when the target entity When the entity category of the entity belongs to the target entity category, the entity information of the target entity includes function entry information; when the entity category of the target entity does not belong to the target entity category, the entity information of the target entity includes function entry information.
  • identification information of multiple target entities, at least one associated media content corresponding to each target entity, encyclopedia knowledge content and/or recommendation information of each target entity, and each target entity are determined based on step S803.
  • a multi-entity aggregation result is generated based on step S804.
  • the entity information of each target entity is aggregated together to generate a multi-entity aggregated result corresponding to the search request.
  • the server aggregates entity information of multiple target entities that meet the user's search request, generates a multi-entity aggregated result, and displays the multi-entity
  • the aggregated results are sent to the client, so that the client can display the above multi-entity aggregated results to the user.
  • the client can display the entity information of multiple target entities that match the search request, and the user can intuitively see multiple targets through the entity aggregation results.
  • the entity information of the entity is convenient for the user to further screen the interested target recommended entity, improve the information search efficiency, and save the search time.
  • the writing order of each step does not mean a strict execution order but constitutes any limitation on the implementation process, and the specific execution order of each step should be based on its function and possible Internal logic is determined.
  • an apparatus for displaying search results corresponding to the method for displaying search results is also provided in the embodiment of the present disclosure. Since the principle of solving the problem of the apparatus in the embodiment of the present disclosure is the same as the above-mentioned method for displaying the search result in the embodiment of the present disclosure Similar, therefore, the implementation of the apparatus may refer to the implementation of the method, and repeated descriptions will not be repeated.
  • the apparatus includes: a sending module 901 , a first acquiring module 902 , and a displaying module 903 ; wherein,
  • the sending module 901 is configured to send a search request in response to a search trigger instruction; the search request corresponds to multiple entities.
  • the first obtaining module 902 is configured to obtain a multi-entity aggregation result corresponding to the search request; wherein, the multi-entity aggregation result includes entity information of multiple target entities matched with the search request; the entity information is Obtained based on the associated media content corresponding to the search request.
  • the display module 903 is configured to display the multi-entity aggregation result.
  • a multi-entity aggregation result corresponding to the search request can be obtained, and the multi-entity aggregation result includes entity information of multiple target entities.
  • the information is obtained based on the associated media content corresponding to the search request.
  • the user terminal can intuitively display the entity information of multiple target entities that match the search request to the user, and the user can easily see the information about the target entities that they are interested in. Entity information improves the efficiency of information search and saves search time.
  • the entity information includes identification information of the target entity and target content information associated with the target entity; wherein the target content information associated with the target entity includes: Among the plurality of associated media contents, at least one associated media content corresponding to the target entity is included.
  • the display module 903 is specifically configured to display the identification information of the multiple target entities in the first display area; determine that the selected target identification information in the identification information of the multiple target entities corresponds to the target recommendation entity; display the content information associated with the target recommendation entity in other display areas.
  • the display module 903 is further specifically configured to display the identification information of the multiple target entities in sequence in the first display area according to the acquired identification information of the multiple target entities.
  • the display module 903 is further specifically configured to display at least one associated media content corresponding to the target recommendation entity in sequence in the second display area.
  • the display module 903 is further specifically configured to use the target entity displayed in the first display position of the first display area as the initial target after acquiring the multi-entity aggregation result recommending entity; if a selection operation is detected for the identification information of other target entities displayed by other display positions in the first display area, the other target entities are regarded as the updated target recommendation entities.
  • the target content information associated with the target entity further includes: encyclopedic knowledge information and/or recommendation information of the target entity.
  • the display module 903 is further specifically configured to display the encyclopedic knowledge information and/or recommendation information of the target recommendation entity in the third display area.
  • the target content information associated with the target entity further includes: function entry information of the target recommendation entity; the function entry information is used to trigger the display of a consumption page corresponding to the target recommendation entity.
  • the display module 903 is further specifically configured to display the function entry information of the target recommended entity in the fourth display area; after detecting a trigger operation for the function entry information, display the function entry information.
  • the display module 903 is further specifically configured to display the function entry information of the target recommended entity in the fourth display area when the entity category of the target recommended entity belongs to the target entity category.
  • the apparatus includes: a receiving module 1001, a second obtaining module 1002, a determining module 1003, and a generating module 1004; wherein,
  • the receiving module 1001 is configured to receive a search request, where the search request corresponds to multiple entities.
  • the second obtaining module 1002 is configured to obtain associated media content matching the search request.
  • the determining module 1003 is configured to determine entity information of multiple target entities according to the associated media content.
  • the generating module 1004 is configured to generate a multi-entity aggregation result corresponding to the search request based on the entity information of the multiple target entities.
  • the entity information includes identification information of the target entity and target content information associated with the target entity; wherein the target content information associated with the target entity includes: Among the plurality of associated media contents, at least one associated media content corresponding to the target entity is included.
  • the server after receiving the user's search request, aggregates entity information of multiple target entities that meet the user's search request, generates a multi-entity aggregation result, and sends the multi-entity aggregation result to the client , so that the user terminal can display the above multi-entity aggregation results to the user, the user terminal can display the entity information of multiple target entities that match the search request, and the user can intuitively see the entity information of multiple target entities through the multi-entity aggregation results. Therefore, it is convenient for the user to further screen the target recommended entities of interest, the efficiency of information search is improved, and the search time is saved.
  • the apparatus further includes an entity extraction module, configured to perform entity extraction on multiple media contents in advance, obtain identification information of the extracted multiple core entities, and store the identification information of each media content Correspondence with the extracted identification information of the core entity.
  • entity extraction module configured to perform entity extraction on multiple media contents in advance, obtain identification information of the extracted multiple core entities, and store the identification information of each media content Correspondence with the extracted identification information of the core entity.
  • the determining module 1003 is specifically configured to determine the entity information of the target entity according to the identification information of the associated media content and the stored corresponding relationship.
  • the determining module 1003 is further specifically configured to search for the identification information of the core entity corresponding to the associated media content according to the identification information of the associated media content and the stored correspondence; Determine the attribute information of the found core entity based on the knowledge graph information corresponding to the identification information of the core entity and the associated media content; based on the intent classification information corresponding to the search request and the attribute information of the core entity , and select the identification information of the target entity from the identification information of the found core entity.
  • the determining module 1003 is further specifically configured to search for classification information corresponding to the identification information of the core entity from the knowledge graph; and the number of times that the core entity appears in different associated media content as the attribute information of the core entity; wherein, the attribute characteristics of the associated media content include: the attribute information of the author, the associated media content and the associated media content. at least one of the degree of correlation between the search requests and the arrangement order of the associated media content in this search.
  • the entity extraction module is specifically configured to perform entity extraction on the multiple media contents based on a pre-trained entity extraction model, and obtain identification information of the extracted multiple core entities; the entity extraction The extraction model is trained based on the media content samples manually marked with the identification information of the core entities.
  • the attribute-based search request refers to a search request that uses multiple attribute keywords to represent search intent.
  • the second obtaining module 1002 is specifically configured to obtain knowledge graph content matching the attribute keywords in the search request;
  • the determining module 1003 is further specifically configured to extract, from the knowledge graph content matching the attribute keywords in the search request, the identification information of the target entity and the Content information associated with the target entity.
  • the target content information associated with the target entity further includes: encyclopedic knowledge content and/or recommendation information; the apparatus further includes a target content information determination module, configured to determine based on the target entity's identification information, to obtain encyclopedic knowledge content matching the identification information of the target entity; and/or, based on the user behavior data and/or author attribute information of each associated media content corresponding to the target entity, determine the content corresponding to the target entity.
  • a target content information determination module configured to determine based on the target entity's identification information, to obtain encyclopedic knowledge content matching the identification information of the target entity; and/or, based on the user behavior data and/or author attribute information of each associated media content corresponding to the target entity, determine the content corresponding to the target entity.
  • a schematic structural diagram of a computer device 1100 provided in an embodiment of the present application includes a processor 1101 , a memory 1102 , and a bus 1103 .
  • the memory 1102 is used to store the execution instructions, including the memory 11021 and the external memory 11022; the memory 11021 here is also called the internal memory, which is used to temporarily store the operation data in the processor 1101 and the data exchanged with the external memory 11022 such as the hard disk,
  • the processor 1101 exchanges data with the external memory 11022 through the memory 11021.
  • the processor 1101 and the memory 1102 communicate through the bus 1103, so that the processor 1101 executes the following instructions:
  • a search request is sent; the search request corresponds to multiple entities; a multi-entity aggregated result corresponding to the search request is obtained; wherein the multi-entity aggregated result includes multiple targets matching the search request entity information of the entity; the entity information is obtained based on the associated media content corresponding to the search request; and the multi-entity aggregation result is displayed.
  • a schematic structural diagram of a computer device 1200 provided in an embodiment of the present application includes a processor 1201 , a memory 1202 , and a bus 1203 .
  • the memory 1202 is used to store the execution instructions, including the memory 12021 and the external memory 12022; the memory 12021 here is also called the internal memory, which is used to temporarily store the operation data in the processor 1201 and the data exchanged with the external memory 12022 such as the hard disk,
  • the processor 1201 exchanges data with the external memory 12022 through the memory 12021.
  • the processor 1201 and the memory 1202 communicate through the bus 1203, so that the processor 1201 executes the following instructions:
  • Receive a search request corresponds to multiple entities; obtain associated media content matching the search request; determine entity information of multiple target entities according to the associated media content; entities based on the multiple target entities information to generate multi-entity aggregated results corresponding to the search request.
  • Embodiments of the present disclosure further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium.
  • a computer program is stored on the computer-readable storage medium.
  • the storage medium may be a volatile or non-volatile computer-readable storage medium.
  • the computer program product of the method for displaying search results provided by the embodiments of the present disclosure includes a computer-readable storage medium storing program codes, and the instructions included in the program codes can be used to perform the displaying of search results described in the foregoing method embodiments.
  • the steps of the method reference may be made to the foregoing method embodiments, which will not be repeated here.
  • Embodiments of the present disclosure also provide a computer program, which implements any one of the methods in the foregoing embodiments when the computer program is executed by a processor.
  • the computer program product can be specifically implemented by hardware, software or a combination thereof.
  • the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (Software Development Kit, SDK), etc. Wait.
  • the units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.
  • each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.
  • the functions, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a processor-executable non-volatile computer-readable storage medium.
  • the technical solutions of the present disclosure can be embodied in the form of software products in essence, or the parts that contribute to the prior art or the parts of the technical solutions.
  • the computer software products are stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present disclosure.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory
  • ROM Read-Only Memory
  • RAM Random Access Memory

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Abstract

一种搜索结果展示的方法、装置及计算机存储介质,其中,方法包括:响应搜索触发指令,发送搜索请求(S101);获取与搜索请求对应的多实体聚合结果(S102);展示多实体聚合结果(S103)。在用户端发起搜索请求后,可以得到与搜索请求对应的多实体聚合结果,在多实体聚合结果中包含多个目标实体的实体信息,这里,多个目标实体的实体信息为基于搜索请求对应的关联媒体内容获取的,如此,用户端可以直观地向用户展示与搜索请求匹配的多个目标实体的实体信息,用户可以方便地看到其中自己感兴趣的目标实体的实体信息,节约了用户搜索时间成本,提高了搜索效率。

Description

一种搜索结果展示的方法、装置及计算机存储介质
相关申请的交叉引用
本申请基于申请号为202010922887.5、申请日为2020年09月04日,名称为“一种搜索结果展示的方法、装置及计算机存储介质”的中国专利申请提出,并要求该中国专利申请的优先权,该中国专利申请的全部内容在此引入本申请作为参考。
技术领域
本公开涉及互联网技术领域,具体而言,涉及一种搜索结果展示的方法、装置及计算机存储介质。
背景技术
随着互联网技术的不断发展,通过终端应用或网站搜索信息已经成为人们获取信息的主要来源。用户在终端应用或网站上发起搜索请求后,会得到一个搜索结果列表,若用户想要在搜索结果列表中找到自己感兴趣的媒体内容,需要挨个查阅搜索结果列表中的每条搜索结果,导致用户搜索时间成本较高,搜索效率较低。
发明内容
本公开实施例至少提供一种搜索结果展示的方法、装置及计算机存储介质。
第一方面,本公开实施例提供了一种搜索结果展示的方法,所述方法包括:
响应搜索触发指令,发送搜索请求;所述搜索请求对应多个实体;
获取与所述搜索请求对应的多实体聚合结果;其中,所述多实体聚合结果包括与所述搜索请求匹配的多个目标实体的实体信息;所述实体信息是基于所述搜索请求对应的关联媒体内容获取的;
展示所述多实体聚合结果。
在一种可能的实施方式中,所述实体信息包括目标实体的标识信息和与目标实体关联的目标内容信息;
其中,所述目标实体关联的目标内容信息包括:在与所述搜索请求对应的多个关联媒体内容中,与所述目标实体对应的至少一个关联媒体内容。
在一种可能的实施方式中,展示所述多实体聚合结果,包括:
在第一展示区域展示所述多个目标实体的标识信息;
确定所述多个目标实体的标识信息中被选中的目标标识信息对应的目标推荐实体;
在其它展示区域展示所述目标推荐实体关联的内容信息。
在一种可能的实施方式中,在第一展示区域展示所述多个目标实体的标识信息,包括:
根据获取的所述多个目标实体的标识信息,在第一展示区域依次展示所述多个目标实体的标识信息。
在一种可能的实施方式中,展示所述多实体聚合结果,包括:
在第二展示区域依次展示所述目标推荐实体对应的至少一个关联媒体内容。
在一种可能的实施方式中,所述确定所述多个目标实体的标识信息中被选中的目标标识信息对应的目标推荐实体,包括:
在获取到所述多实体聚合结果后,将在所述第一展示区域的第一个展示位展示的目标实体作为初始的目标推荐实体;
若检测到针对所述第一展示区域的其它展示位展示的其它目标实体的标识信息的选中操作,将所述其它目标实体作为更新后的目标推荐实体。
在一种可能的实施方式中,所述目标实体关联的目标内容信息还包含:所述目标实体的百科知识信息和/或推荐信息。
在一种可能的实施方式中,展示所述多实体聚合结果,包括:
在第三展示区域展示所述目标推荐实体的所述百科知识信息和/或推荐信息。
在一种可能的实施方式中,所述目标实体关联的目标内容信息还包含:所述目标推荐实体的功能入口信息;所述功能入口信息用于触发展示所述目标推荐实体对应的消费页面。
在一种可能的实施方式中,展示所述多实体聚合结果,包括:
在第四展示区域展示所述目标推荐实体的功能入口信息;
在检测到针对所述功能入口信息的触发操作后,展示所述目标推荐实体对应的消费页面。
在一种可能的实施方式中,在第四展示区域展示所述目标推荐实体的功能入口信息,包括:
在所述目标推荐实体的实体类别属于目标实体类别的情况下,在第四展示区域展示所述目标推荐实体的功能入口信息。
第二方面,本公开实施例还提供了一种搜索结果展示的方法,所述方法包括:
接收搜索请求,所述搜索请求对应多个实体;
获取与所述搜索请求匹配的关联媒体内容;
根据所述关联媒体内容,确定多个目标实体的实体信息;
基于所述多个目标实体的实体信息,生成与搜索请求对应的多实体聚合结果。
在一种可能的实施方式中,所述实体信息包括目标实体的标识信息和与目标实体关联的目标内容信息;
其中,所述目标实体关联的目标内容信息包含:在与所述搜索请求对应的多个关联媒体内容中,与所述目标实体对应的至少一个关联媒体内容。
在一种可能的实施方式中,所述方法还包括:
预先对多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息,并存储每个媒体内容的标识信息与提取的核心实体的标识信息之间的对应关系;
所述根据所述关联媒体内容,确定目标实体的实体信息,包括:
根据所述关联媒体内容的标识信息,以及存储的所述对应关系,确定目标实体的实体信息。
在一种可能的实施方式中,根据所述关联媒体内容的标识信息,以及存储的所述对应关系,确定目标实体的实体信息,包括:
根据所述关联媒体内容的标识信息,以及存储的所述对应关系,查找与所述关联媒体内容对应的核心实体的标识信息;
基于与所述核心实体的标识信息对应的知识图谱信息和所述关联媒体内容,确定查找到的核心实体的属性信息;
基于所述搜索请求对应的意图分类信息,和所述核心实体的属性信息,从查找到的核心实体的标识信息中选择目标实体的标识信息。
在一种可能的实施方式中,基于与所述核心实体的标识信息对应的知识图谱信息和所述关联媒体内容,确定查找到的核心实体的属性信息,包括:
从知识图谱中查找与所述核心实体的标识信息对应的分类信息;
将所述分类信息、所述核心实体对应的关联媒体内容的属性特征、以及所述核心实体在不同关联媒体内容中出现的次数作为所述核心实体属性信息;
其中,所述关联媒体内容的属性特征包括:作者的属性信息、所述关联媒体内容与所述搜索请求之间的相关度、所述关联媒体内容在本次搜索中的排列顺序位中的至少一种。
在一种可能的实施方式中,所述预先对多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息,包括:
基于预先训练的实体提取模型对所述多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息;所述实体提取模型为基于人工标注好核心实体的标识信息的媒体内容样本训练得到的。
在一种可能的实施方式中,若所述搜索请求为属性类搜索请求,所述属性类搜索请求是指使用多个属性关键词来表征搜索意图的搜索请求,所述获取与所述搜索请求匹配的关联媒体内容,包括:
获取与所述搜索请求中的属性关键词匹配的知识图谱类内容;
所述根据所述关联媒体内容,确定所述目标实体的标识信息以及与所述目标实体关联的内容信息,包括:
从与所述搜索请求中的属性关键词匹配的知识图谱类内容中,提取用于展示在所述多实体聚合结果中的所述目标实体的标识信息以及所述目标实体关联的内容信息。
在一种可能的实施方式中,与所述目标实体关联的目标内容信息还包括:百科知识内容和/或推荐信息;
根据以下步骤确定所述百科知识内容和/或推荐信息:
基于所述目标实体的标识信息,获取与所述目标实体的标识信息匹配的百科知识内容;和/或,
基于所述目标实体对应的各个关联媒体内容的用户行为数据和/或作者属性信息,确定与目标实体对应的推荐信息。
第三方面,本公开实施例还提供了一种搜索结果展示的装置,包括:
发送模块,用于响应搜索触发指令,发送搜索请求;所述搜索请求对应多个实体;
第一获取模块,用于获取与所述搜索请求对应的多实体聚合结果;其中,所述多实体聚合结果包括与所述搜索请求匹配的多个目标实体的实体信息;所述实体信息是基于所述搜索请求对应的关联媒体内容获取的;
展示模块,用于展示所述多实体聚合结果。
在一种可能的实施方式中,所述实体信息包括目标实体的标识信息和与目标实体关联的目标内容信息;其中,所述目标实体关联的目标内容信息包含:在与所述搜索请求对应的多个关联媒体内容中,与所述目标实体对应的至少一个关联媒体内容。
在一种可能的实施方式中,所述展示模块,具体用于在第一展示区域展示所述多个目标实体的标识信息;确定所述多个目标实体的标识信息中被选中的目标标识信息对应的目标推荐实体;在其它展示区域展示所述目标推荐实体关联的内容信息。
在一种可能的实施方式中,所述展示模块,还具体用于根据获取的所述多个目标实体的标识信息,在第一展示区域依次展示所述多个目标实体的标识信息。
在一种可能的实施方式中,所述展示区域,还具体用于在第二展示区域依次展示所述目标推荐实体对应的至少一个关联媒体内容。
在一种可能的实施方式中,所述展示模块,还具体用于在获取到所述多实体聚合结果后,将在所述第一展示区域的第一个展示位展示的目标实体作为初始的目标推荐实体;
若检测到针对所述第一展示区域的其它展示位展示的其它目标实体的标识信息的选中操作,将所述其它目标实体作为更新后的目标推荐实体。
在一种可能的实施方式中,所述目标实体关联的目标内容信息还包含:所述目标实体的百科知识信息和/或推荐信息。
在一种可能的实施方式中,所述展示模块,还具体用于在第三展示区域展示所述目标推荐实体的所述百科知识信息和/或推荐信息。
在一种可能的实施方式中,所述目标实体关联的目标内容信息还包含:所述目标推荐实体的功能入口信息;所述功能入口信息用于触发展示所述目标推荐实体对应的消费页面。
在一种可能的实施方式中,所述展示模块,还具体用于在第四展示区域展示所述目标推荐实体的功能入口信息;在检测到针对所述功能入口信息的触发操作后,展示所述目标推荐实体对应的消费页面。
在一种可能的实施方式中,所述展示模块,还具体用于在所述目标推荐实体的实体类别属于目标实体类别的情况下,在第四展示区域展示所述目标推荐实体的功能入口信息。
第四方面,本公开实施例还提供了一种搜索结果展示的装置,包括:
接收模块,用于接收搜索请求,所述搜索请求对应多个实体。
第二获取模块,用于获取与所述搜索请求匹配的关联媒体内容。
确定模块,用于根据所述关联媒体内容,确定多个目标实体的实体信息。
生成模块,用于基于所述多个目标实体的实体信息,生成与搜索请求对应的多实体聚合结果。
在一种可能的实施方式中,所述实体信息包括目标实体的标识信息和与目标实体关联的目标内容信息;
其中,所述目标实体关联的目标内容信息包含:在与所述搜索请求对应的多个关联媒体内容中,与所述目标实体对应的至少一个关联媒体内容。
在一种可能的实施方式中,所述装置还包括实体提取模块,用于预先对多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息,并存储每个媒体内容的标识信息与提取的核心实体的标识信息之间的对应关系;
所述确定模块,具体用于根据所述关联媒体内容的标识信息,以及存储的所述对应关系,确定目标实体的实体信息。
在一种可能的实施方式中,所述确定模块,还具体用于根据所述关联媒体内容的标识信息,以及存储的所述对应关系,查找与所述关联媒体内容对应的核心实体的标识信息;基于与所述核心实体的标识信息对应的知识图谱信息和所述关联媒体内容,确定查找到的核心实体的属性信息;基于所述搜索请求对应的意图分类信息,和所述核心实体的属性信息,从查找到的核心实体的标识信息中选择目标实体的标识信息。
在一种可能的实施方式中,所述确定模块,还具体用于从知识图谱中查找与所述核心实体的标识信息对应的分类信息;将所述分类信息、所述核心实体对应的关联媒体内容的属性特征、以及所述核心实体在不同关联媒体内容中出现的次数作为所述核心实体属性信息;其中,所述关联媒体内容的属 性特征包括:作者的属性信息、所述关联媒体内容与所述搜索请求之间的相关度、所述关联媒体内容在本次搜索中的排列顺序位中的至少一种。
在一种可能的实施方式中,所述实体提取模块,具体用于基于预先训练的实体提取模型对所述多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息;所述实体提取模型为基于人工标注好核心实体的标识信息的媒体内容样本训练得到的。
在一种可能的实施方式中,若所述搜索请求为属性类搜索请求,所述属性类搜索请求是指使用多个属性关键词来表征搜索意图的搜索请求,所述第二获取模块,具体用于获取与所述搜索请求中的属性关键词匹配的知识图谱类内容;
所述确定模块,还具体用于从与所述搜索请求中的属性关键词匹配的知识图谱类内容中,提取用于展示在所述多实体聚合结果中的所述目标实体的标识信息以及所述目标实体关联的内容信息。
在一种可能的实施方式中,与所述目标实体关联的目标内容信息还包括:百科知识内容和/或推荐信息;
所述装置还包括目标内容信息确定模块,用于基于所述目标实体的标识信息,获取与所述目标实体的标识信息匹配的百科知识内容;和/或,基于所述目标实体对应的各个关联媒体内容的用户行为数据和/或作者属性信息,确定与目标实体对应的推荐信息。
第五方面,本公开实施例还提供一种计算机设备,包括:处理器、存储器和总线,所述存储器存储有所述处理器可执行的机器可读指令,当计算机设备运行时,所述处理器与所述存储器之间通过总线通信,所述机器可读指令被所述处理器执行时执行上述第一方面,或第一方面中任一种可能的实施方式中的步骤,或执行上述第二方面,或第二方面中任一种可能的实施方式中的步骤。
第六方面,本公开实施例还提供一种计算机可读存储介质,该计算机可读存储介质上存储有计算机程序,该计算机程序被处理器运行时执行上述第一方面,或第一方面中任一种可能的实施方式中的步骤,或执行上述第二方面,或第二方面中任一种可能的实施方式中的步骤。
本公开实施例提供的搜索结果展示的方法、装置及计算机存储介质,当用户在用户端发起搜索请求时,可以得到与搜索请求对应的多实体聚合结果,在该多实体聚合结果中包含与搜索请求匹配的多个目标实体的实体信息,用 户端可以直观地将与搜索请求匹配的多个目标实体的实体信息展示给用户,用户通过聚合结果可以直观地看到多个目标实体,从而方便了用户进一步筛选感兴趣的目标实体,提高了信息查找效率,节省了搜索时间。
关于上述搜索结果展示的装置、电子设备、及计算机可读存储介质的效果描述参见上述搜索结果展示的方法的说明,这里不再赘述。
为使本公开的上述目的、特征和优点能更明显易懂,下文特举较佳实施例,并配合所附附图,作详细说明如下。
附图说明
为了更清楚地说明本公开实施例的技术方案,下面将对实施例中所需要使用的附图作简单地介绍,此处的附图被并入说明书中并构成本说明书中的一部分,这些附图示出了符合本公开的实施例,并与说明书一起用于说明本公开的技术方案。应当理解,以下附图仅示出了本公开的某些实施例,因此不应被看作是对范围的限定,对于本领域普通技术人员来讲,在不付出创造性劳动的前提下,还可以根据这些附图获得其他相关的附图。
图1示出了本公开实施例所提供的一种搜索结果展示的方法的流程图;
图2示出了本公开实施例所提供的一种第一展示区域的展示界面的示意图;
图3示出了本公开实施例所提供的一种搜索结果的展示界面的示意图;
图4示出了本公开实施例所提供的另一种搜索结果的展示界面的示意图;
图5示出了本公开实施例所提供的一种关联媒体内容的详情页面的展示界面的示意图;
图6示出了本公开实施例所提供的目标推荐实体对应的一种消费页面的展示界面的示意图;
图7示出了本公开实施例所提供的目标推荐实体对应的另一种消费页面的展示界面的示意图;
图8示出了本公开实施例所提供的另一种搜索结果展示的方法的流程图;
图9示出了本公开实施例所提供的一种搜索结果展示的装置的示意图;
图10示出了本公开实施例所提供的另一种搜索结果展示的装置的示意图;
图11示出了本公开实施例所提供的一种计算机设备的示意图;
图12示出了本公开实施例所提供的另一种计算机设备的示意图。
具体实施方式
为使本公开实施例的目的、技术方案和优点更加清楚,下面将结合本公开实施例中附图,对本公开实施例中的技术方案进行清楚、完整地描述,显然,所描述的实施例仅仅是本公开一部分实施例,而不是全部的实施例。通常在此处附图中描述和示出的本公开实施例的组件可以以各种不同的配置来布置和设计。因此,以下对在附图中提供的本公开的实施例的详细描述并非旨在限制要求保护的本公开的范围,而是仅仅表示本公开的选定实施例。基于本公开的实施例,本领域技术人员在没有做出创造性劳动的前提下所获得的所有其他实施例,都属于本公开保护的范围。
经研究发现,用户在终端应用或网站上搜索自己感兴趣的媒体内容时,用户只能在终端屏幕上查看到由多条搜索结果构成的搜索结果列表,其中,每条搜索结果都包含:搜索结果网页的标题、该搜索结果简要介绍等。用户需要在搜索列表中挨个查阅才能找到符合自己搜索需求的搜索结果,导致用户搜索时间成本较高,搜索效率较低。
基于上述研究,本公开实施例提供了一种搜索结果展示的方法、装置及计算机存储介质,当用户在用户端发起搜索请求时,服务器会将符合用户搜索请求的多个目标实体的实体信息聚合在一起,生成多实体聚合结果,并将多实体聚合结果发送给用户端,用户端展示上述多实体聚合结果,这样,用户通过多实体聚合结果可以一下子看到多个目标实体,从而方便了用户快速定位感兴趣的目标实体,提高了信息查找效率,节省了搜索时间。另外,本公开实施例中,多实体聚合结果可以包含每个目标实体的标识信息以及每个目标实体关联的目标内容信息,用户端可以展示与搜索请求匹配的多个推荐实体的标识信息,用户可以从中选择自己感兴趣的目标推荐实体,基于用户选择的感兴趣的目标推荐实体,在当前页面中可以展示出与该目标推荐实体关联的内容信息,从而便于用户快速查看自己感兴趣的目标实体的相关信息。
针对以上方案所存在的缺陷,均是发明人在经过实践并仔细研究后得出的结果,因此,上述问题的发现过程以及下文中本公开针对上述问题所提出的解决方案,都应该是发明人在本公开过程中对本公开做出的贡献。
应注意到:相似的标号和字母在下面的附图中表示类似项,因此,一旦某一项在一个附图中被定义,则在随后的附图中不需要对其进行进一步定义和解释。
为便于对本实施例进行理解,首先对本公开实施例所公开的一种搜索结果展示的方法进行详细介绍,本公开实施例所提供的搜索结果展示的方法的执行主体一般为具有一定计算能力的计算机设备,该计算机设备例如包括:终端设备或服务器或其它处理设备,终端设备可以为用户设备(User
Equipment,UE)、移动设备、用户终端、终端、蜂窝电话、无绳电话、个人数字处理(Personal Digital Assistant,PDA)、手持设备、计算设备、车载设备、可穿戴设备等。在一些可能的实现方式中,该搜索结果展示的方法可以通过处理器调用存储器中存储的计算机可读指令的方式来实现。
实施例一
下面以执行主体为用户端为例对本公开实施例提供的搜索结果展示的方法加以说明。
这里,用户端可以为终端设备、平板电脑、计算机设备等具有显示功能的电子设备;其中,终端设备可以为用户设备(User Equipment,UE)、移动设备、用户终端、终端、无绳电话、个人数字处理(Personal Digital Assistant,PDA)、手持设备、计算设备、车载设备等。
参见图1所示,为本公开实施例提供的搜索结果展示的方法的流程图,所述方法包括步骤S101~S103,其中:
S101、响应搜索触发指令,发送搜索请求。
其中,搜索触发指令可以为用户在搜索页面中对搜索按钮执行点击操作发起的。
这里,搜索请求中携带有用户输入的搜索内容,可以代表用户的搜索意图。本公开实施例处理的搜索请求是涉及多个实体的,比如,用户搜索“适合情侣看的电影”,这个搜索请求对应多个电影实体。
在具体实施中,用户在用户端的搜索页面输入搜索内容,并点击“搜索”按钮后,用户端会将用户的搜索请求发送给服务器。
在具体实施中,当用户端将用户的搜索请求发送给服务器后,服务器可以获取与搜索请求匹配的关联媒体内容,并根据关联媒体内容,确定多个目标实体的实体信息,基于多个目标实体的实体信息,生成与搜索请求对应的多实体聚合结果,并将该多实体聚合结果返回给用户端,详见关于服务器侧实施例的描述。
S102、获取与所述搜索请求对应的多实体聚合结果。
如前所述,用户端获取的多实体聚合结果中包括与搜索请求匹配的多个目标实体的实体信息,实体信息是基于所述搜索请求对应的关联媒体内容获取的。
这里,实体信息可以包括目标实体的标识信息和与目标实体关联的目标内容信息。
其中,目标实体的标识信息可以包括实体标识号、实体名称、以及表征目标实体的缩略图,还可以包括该目标实体在多实体聚合结果包含的多个目标实体中的排列顺序位的标号等;其中,实体的缩略图可以为宣传图片、介绍图片等;
与目标实体关联的目标内容信息可以包括:在与搜索请求对应的多个关联媒体内容中,获取到的与目标实体对应的至少一个关联媒体内容,也即,本公开实施例可以在展示多个目标实体的标识信息的同时,还可以将与用户的搜索请求对应的关联媒体内容进行同步展示。
除此之外,与目标实体关联的目标内容信息还可以包括:目标实体的百科知识信息和/或推荐信息、和/或,目标实体对应的功能入口信息;这里,推荐信息可以为对该目标实体的文本简介内容、图文简介内容、视频或音频介绍内容等;功能入口信息可以用来指示用户点击进入该目标实体的详情页面,该详情页面可以为该目标实体的具体展示界面,也可以为该目标实体对应的购买页面。
在具体实施中,根据实体类别的不同,可以有选择性地进行上述百科知识信息和/或推荐信息,和/或上述功能入口信息的展示。实体类别比如包括影视类、商品类、科普类、音乐类、菜谱类等。比如,针对菜谱类可以不需要 展示百科知识信息和/或推荐信息,对于影视类和科普类的则展示百科知识信息和/或推荐信息。再比如,针对影视类、商品类、和音乐类的实体类别,可以展示功能入口信息。
S103、展示所述多实体聚合结果。
在具体实施中,在基于步骤S102接收到多实体聚合结果后,根据获取的多实体聚合结果中多个目标实体的标识信息,在用户端的第一展示区域可以依次展示多个目标实体的标识信息。
这里,标识信息可以包括实体名称、以及表征实体的缩略图、以及每个实体在多实体聚合结果中的排列顺序位。
比如:当用户在用户端屏幕上输入搜索内容为“夜间适合情侣看的电影”后,用户端接收到的多实体聚合结果中涉及影视作品“情迷六月花”、“返老还童”、“恋恋笔记本”、“西西里的美丽传说”这多个目标实体。用户端根据多个目标实体的排列顺序位,在第一展示区域依次展示“情迷六月花”的名称和缩略图、“返老还童”的名称和缩略图、“恋恋笔记本”的名称和缩略图、“西西里的美丽传说”的名称和缩略图,除此之外,还可以展示“情迷六月花”、“返老还童”、“恋恋笔记本”、“西西里的美丽传说”的排列顺序位的标号,具体第一展示区域的展示页面以用户端为手机为例,参照图2所示。
在具体实施中,在用户端的第一展示区域展示多个目标实体的标识信息后,确定多个目标实体的标识信息中被选中的目标标识信息对应的目标推荐实体,在其他展示区域展示该目标推荐实体关联的内容信息。
这里,一方面考虑到屏幕展示空间有限,另一方面为了方便用户聚焦到自己感兴趣的目标实体上,本公开实施例中,用户可以在第一展示区域展示的多个目标实体中快速定位并选择自己感兴趣的目标推荐实体,用户端在确认用户感兴趣的目标推荐实体后,可以在其他展示区域展示与用户选中的目标推荐实体关联的内容信息。
另外,在获取到多实体聚合结果后,当用户还没有在第一展示区域展示的多个目标实体的标识信息中选择自己感兴趣的目标实体时,可以将在第一展示区域的第一个展示位的目标实体作为默认的初始目标推荐实体。当用户端检测到针对第一展示区域的其它展示位展示的其它目标实体的标识信息的选中操作后,再将该其它目标实体作为更新后的目标推荐实体。
也即,当目标推荐实体为多个目标实体中排列在第一个展示位的目标实体时,则在其它展示区域展示排列在第一个展示位的目标推荐实体关联的内容信息。当用户端检测到针对第一展示区域的其它展示位展示的其它目标实体的标识信息的选中操作后,将该其它目标实体作为更新后的目标推荐实体,并在其它展示区域展示更新后的目标推荐实体关联的内容信息。
其中,目标推荐实体关联的内容信息可以包括与该目标推荐实体对应的至少一个关联媒体内容、该目标推荐实体的百科知识信息和/或推荐信息、以及该目标实体对应的功能入口信息。推荐信息可以包括目标推荐实体的文本简介、图文简介、视频或音频介绍等,百科知识信息为介绍目标推荐实体的百科知识内容。
具体地,可以根据目标推荐实体对应的至少一个关联媒体内容的排列顺序,在第二展示区域展示该目标推荐实体对应的至少一个关联媒体内容。以及,可以在第三展示区域展示该目标推荐实体的百科知识信息和/或推荐信息。以及,当目标推荐实体为影视、商品或音乐类别的目标实体时,目标推荐实体关联的内容信息中还包含功能入口信息,可以在第四展示区域展示该目标推荐实体的功能入口信息。
具体的,用户端展示多实体聚合结果的过程如下所述:将多实体聚合结果中包含的每个目标实体的实体名称、每个目标实体对应的缩略图,按照每个目标实体的排列顺序位在第一展示区域展示,同时,将在第一展示区域的第一个展示位展示的目标实体作为初始目标推荐实体,在其他展示区域展示初始目标推荐实体关联的目标内容信息。当检测到用户选中其他目标实体后,将用户选中的目标实体作为新的目标推荐实体,在其他展示区域展示新的目标推荐实体关联的目标内容信息;具体地,根据该目标推荐实体对应的多个关联媒体内容的排列顺序以及用户端屏幕尺寸大小,在第二展示区域展示该目标推荐实体对应的排列靠前的至少一个关联媒体内容;在第三展示区域展示该目标推荐实体的百科知识信息和/或推荐信息;在目标推荐实体的实体类别属于目标实体类别的情况下,在第四展示区域展示该目标推荐实体的功能入口信息。这里,作为一种实施方式,当目标推荐实体不属于目标实体类别时,在目标推荐实体关联的内容信息中可以不包含功能入口信息,也即可以不用有第四展示区域。
示例性地,当用户在用户端屏幕上输入搜索内容为“夜间适合情侣看的电影”时,服务器根据用户的搜索请求,确定符合用户搜索请求的多个目标实体分别为影视作品:“情迷六月花”、“返老还童”、“恋恋笔记本”、“西西里的美丽传说”,且上述多个目标实体对应实体类别均属于上述所述的目标实体类别,服务器基于上述多个目标实体生成多实体聚合结果,并将该多实体聚合结果返回给用户端,用户端基于多实体聚合结果中多个目标实体的标识信息,在第一展示区域依次展示“情迷六月花”、“返老还童”、“恋恋笔记本”、“西西里的美丽传说”的实体名称、实体缩略图以及排列顺序位的标号;当用户没有选中第一展示区域展示的多个目标实体中的任一目标实体的标识信息时,将“情迷六月花”作为默认初始的目标推荐实体,并在第二展示区域展示与“情迷六月花”有关的文章介绍内容、影视评论内容以及精彩片段内容等关联媒体内容;在第三展示区域展示“情迷六月花”对应的影视简要介绍内容和指示用户查看该影视作品的百科知识的指示信息“查看百科信息”(这里,用户点击“查看百科信息”后,可以跳转到该影视作品对应的百科知识详情页面),在第四展示区域展示指示用户操作的功能入口信息(这里,功能入口信息可以为:观看“情迷六月花”)。具体搜索结果的展示界面以用户端为手机为例,如图3所示。
示例性地,当用户在用户端屏幕上输入搜索内容为“夜间适合情侣看的电影”时,服务器根据用户的搜索请求,确定符合用户搜索请求的多个目标实体分别为影视作品:“情迷六月花”、“返老还童”、“恋恋笔记本”、“西西里的美丽传说”,且上述多个目标实体对应实体类别均属于目标实体类别,服务器基于上述多个目标实体生成多实体聚合结果,并将该多实体聚合结果返回给用户端,用户端基于多实体聚合结果中多个目标实体的标识信息,在第一展示区域依次展示“情迷六月花”、“返老还童”、“恋恋笔记本”、“西西里的美丽传说”的实体名称、实体缩略图以及排列顺序位;当用户在第一展示区域选中多个目标实体中的“西西里的美丽传说”的标识信息时,则将“西西里的美丽传说”作为目标推荐实体,并在第二展示区域展示与“西西里的美丽传说”有关的文章介绍内容、影视评论内容以及精彩片段内容等关联媒体内容;在第三展示区域展示“西西里的美丽传说”对应的影视简要介绍内容和指示用户查看该影视作品的百科知识的指示信息“查看百科信息”(这 里,用户点击“查看百科信息”后,可以跳转到该影视作品对应的百科知识详情页面),在第四展示区域展示指示用户操作的功能入口信息(这里,功能入口信息可以为观看“西西里的美丽传说”)。具体搜索结果的展示界面以用户端为手机为例,如图4所示。
本公开实施例提供的搜索结果展示的方法中,当用户在用户端发起搜索请求时,可以得到与搜索请求对应的多实体聚合结果,在该多实体聚合结果中包含与搜索请求匹配的多个目标实体的实体信息,用户端可以直观地将与搜索请求匹配的多个目标实体的实体信息展示给用户,用户通过聚合结果可以直观地看到多个目标实体,从而方便了用户进一步筛选感兴趣的目标实体,提高了信息查找效率,节省了搜索时间。
在一种可选的实施方式中,在第二展示区域展示目标推荐实体对应的至少一个关联媒体内容之后,还包括:响应针对任一关联媒体内容的选中操作,展示所述任一关联媒体内容的详情页面。
具体的,当用户选中屏幕上展示的该目标推荐实体的关联媒体内容后,则跳转至该关联媒体内容的详情页面,并在用户端屏幕上展示该关联媒体内容的详情页面。
示例性地,当用户在用户端屏幕上输入搜索内容为“夜间适合情侣看的电影”并发起搜索请求后,用户端接收到多实体聚合结果,基于多实体聚合结果中多个目标实体的标识信息,在第一展示区域依次展示“情迷六月花”、“返老还童”、“恋恋笔记本”、“西西里的美丽传说”的实体名称、实体缩略图以及排列顺序位的标号;默认将“情迷六月花”作为目标推荐实体,在第二展示区域展示与“情迷六月花”相关的影视评论内容的简介信息、以及精彩片段内容的简介信息等关联媒体内容,在第三展示区域展示“情迷六月花”对应的百科知识信息,在第四展示区域展示指示用户操作的功能入口信息。当用户在上述第二展示区域中的“情迷六月花”的影视评论内容和精彩片段内容中,选中影视评论内容后,在用户端屏幕上展示该影视评论内容的详情页面。具体详情页面可以为图5所示的界面展示图,以用户端为手机为例。
在一种可选的实施方式中,在第四展示区域展示所述目标推荐实体的功能入口信息之后,还包括:在检测到针对所述功能入口信息的触发操作后, 响应针对所述功能入口信息的触发操作,展示所述目标推荐实体对应的消费页面。
其中,触发操作可以为双击操作、单击操作等选中操作。
其中,消费页面可以为播放或购买页面,也可以为具体的播放或展示该推荐实体的详情页面。
具体的,当用户选中屏幕上展示的该目标推荐实体功能入口信息后,则跳转至该关联媒体内容的消费页面,并在用户端屏幕上展示该目标推荐实体对应的消费页面。
示例性地,用户端发起对应多个实体的搜索请求后,获取多实体聚合结果,在第一展示区域依次展示多个目标实体“情迷六月花”、“返老还童”、“恋恋笔记本”、“西西里的美丽传说”的实体名称、实体缩略图以及排列顺序位的标号;当用户选中第一展示区域展示的多个目标实体中的“返老还童”的标识信息时,将“返老还童”作为目标推荐实体,在第二展示区域展示与“返老还童”相关的影视评论内容、以及精彩片段内容等关联媒体内容,在第三展示区域展示“返老还童”对应的百科知识信息,在第四展示区域展示指示用户操作的功能入口信息。当在用户点击该功能入口信息后,则跳转至“返老还童”影视作品的消费页面,并在用户端屏幕上展示包括实体名称:“返老还童”、实体缩略图、以及购买提示语“该影视内容付费后才能观看,请购买”,以及购买按键、试看按键的“返老还童”的消费页面。具体消费页面可以为图6所示的界面展示图,以用户端为手机为例;或者,当“返老还童”影视作品为免费观看作品时,在用户点击该功能入口信息后,则跳转至播放“返老还童”影视作品的详情页面,并在用户端屏幕上展示“返老还童”影视作品的详情页面;其中,“返老还童”影视作品的详情页面可以包括实体名称:“返老还童”、具体影视内容、该影视内容的简介、以及已观看用户的评论内容等。具体消费页面可以为图7所示的界面展示图,以用户端为手机为例。
下面以执行主体为服务器为例对本公开实施例提供的搜索结果展示的方法加以说明。
参见图8所示,为本公开实施例提供的一种搜索结果展示的方法的流程图,可以应用于服务器,所述方法包括步骤S801~S804,其中:
S801、接收搜索请求。
其中,所述搜索请求对应多个实体。
S802、获取与所述搜索请求匹配的关联媒体内容。
其中,关联媒体内容可以为一个或多个媒体内容;关联媒体内容可以为文本文档、图文混合文档、图片、视频、音频等。
其中,所述搜索请求的请求类型可以包括属性类、实体集合类。
在一种可能的实施方式中,若所述搜索请求为属性类搜索请求,则可以根据搜索请求中包含的多个属性关键词,获取与搜索请求中的属性关键词匹配的知识图谱类内容。
其中,所述属性类搜索请求是指使用多个属性关键词来表征搜索意图的搜索请求。比如:当用户在搜索页面中输入的搜索内容为“90后中身高170cm的女明星”时,这里的多个属性关键词“90后”、“身高”、“170cm”、“女明星”表征了用户的搜索意图。
其中,知识图谱可以为由多个节点和节点之间的连接边构成的语义网络,这里,节点可以代表实体,节点的信息即为对应的实体的相关信息,节点之间的连接边可以代表实体之间的各种语义关系,比如父母关系、夫妻关系、经纪人、好友等等。
示例性地,当用户在搜索页面中输入的搜索内容为“90后中身高170cm的女明星”,并点击“搜索”按钮后,用户端将搜索请求发送给服务器,服务器接收上述搜索请求,确定该搜索请求类型为属性类搜索请求,提取该搜索请求对应的搜索内容中包含的多个属性关键词为“90后”、“身高”、“170cm”、“女明星”,基于上述多个属性关键词,获取知识图谱中匹配上述性别、年龄、身高属性的关联媒体内容,并将查找出的关联媒体内容反馈给用户。
在具体实施中,可以通过以下方法确定与所述搜索请求匹配的多个关联媒体内容,具体描述如下:在搜索请求对应的查询意图为客观类意图的情况下,查找具有与该搜索请求匹配的客观答案的关联媒体内容;在搜索请求对应的查询意图为主观类意图的情况下,查找具有与该搜索请求匹配的主观类搜索结果的关联媒体内容。
这里,搜索请求对应的查询意图类型可以包括客观类意图和主观类意图。针对客观类意图的搜索请求,召回的为包含客观答案的关联媒体内容,而对 于主观类意图的搜索请求,召回的为发表的相关主观类观点内容的关联媒体内容。在针对这两类搜索请求进行关联媒体内容的查找时,都可以采用标准语义提取的方式,得到搜索请求对应的标准语句,进一步查找与得到的标准语句匹配的关联媒体内容。
具体地,可以基于预先训练的泛化模型,确定与所述搜索请求中的搜索语句对应的标准语句;然后基于该标准语句,获取与搜索请求匹配的关联媒体内容。这里的泛化模型为基于大量标注有标准语句的搜索语句样本训练得到的,泛化模型可以先对搜索语句进行关键词提取,进而将提取的关键词转换为标准语句。
比如,当用户在搜索页面输入的搜索内容为:“四大名著有哪些”或“四大名著包含什么”时,服务器中预先训练的泛化模型对上述搜索内容“四大名著有哪些”或“四大名著包含什么”进行关键词提取,提取上述搜索内容对应的搜索关键词“四大名著”,并形成标准语句“四大名著是什么”。
具体的,服务器接收到用户的搜索请求之后,将该搜索请求对应的搜索内容输入到泛化模型中,确定该搜索请求对应的标准语句,并基于该标准语句,查询媒体内容库,确定与该搜索请求对应的多个关联媒体内容。
示例性地,用户在搜索界面输入的搜索内容为:“四大名著有哪些”,当用户点击“搜索”按钮后,服务器将上述搜索内容“四大名著有哪些”输入到泛化模型中,确定上述搜索内容对应的标准语句为“四大名著是什么”,基于该标准语句,在媒体内容库中查询与该搜索内容匹配的关联媒体内容。
在具体实施中,在基于步骤S802获取到与搜索请求匹配的关联媒体内容之后,可以通过步骤S803,确定与搜索请求匹配的多个目标实体的实体信息,具体描述如下。
S803、根据所述关联媒体内容,确定多个目标实体的实体信息。
这里,实体信息中可以包含目标实体的标识信息、与目标实体关联的目标内容信息等。
其中,目标实体的标识信息可以包括实体标识号、实体名称、以及表征目标实体的缩略图,还可以包括该目标实体在多实体聚合结果包含的多个目标实体中的排列顺序位的标号等;其中,实体的缩略图可以为宣传图片、介绍图片等;
与目标实体关联的目标内容信息可以包括:在与搜索请求对应的多个关联媒体内容中,获取到的与目标实体对应的至少一个关联媒体内容、该目标实体的百科知识信息和/或推荐信息、以及该目标实体对应的功能入口信息;其中,推荐信息可以为对该目标实体的文本简介内容、图文简介内容、视频或音频介绍内容等;功能入口信息可以用来指示用户点击进入该目标实体的详情页面,该详情页面可以为该目标实体的具体展示界面,也可以为该目标实体对应的购买页面。
这里,服务器预先对多个媒体内容分别进行实体提取,得到提取的多个核心实体的标识信息,并存储每个媒体内容的标识信息与提取的核心实体的标识信息之间的对应关系;
其中,核心实体的标识信息可以包括实体名称、实体缩略图、实体标识号等信息;媒体内容的标识信息可以包括媒体内容的标题信息、媒体内容的访问地址等。
这里,可以基于预先训练的实体提取模型对所述多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息;其中,实体提取模型为基于人工标注好核心实体的标识信息的媒体内容样本训练得到的。
在具体实施中,服务器根据步骤S802获取到关联媒体内容的标识信息,以及存储的每个关联媒体内容的标识信息与提取的核心实体的标识信息之间的对应关系,查找与每个关联媒体内容对应的核心实体的标识信息;并基于核心实体的标识信息对应的知识图谱信息和关联媒体内容,确定查找到的核心实体的属性信息;并基于所述搜索请求对应的意图分类信息,和所述核心实体的属性信息,从查找到的核心实体的标识信息中选择目标实体的标识信息。
这里,可以通过以下方法确定查找到的核心实体的属性信息,具体描述如下:从知识图谱中查找与所述核心实体的标识信息对应的分类信息;将所述分类信息、所述核心实体对应的关联媒体内容的属性特征、以及所述核心实体在不同关联媒体内容中出现的次数等作为所述核心实体属性信息;
其中,所述关联媒体内容的属性特征包括:作者的属性信息、所述关联媒体内容与所述搜索请求之间的相关度、所述关联媒体内容在本次搜索中的排列顺序位中的至少一种。
知识图谱中存储有每个实体的标识信息、以及每个实体的分类信息。其中,分类信息可以表征候选实体的类型,可以包括文学、书籍、电影、艺术、生活、交通工具、汽车、社会、品牌、美食、商品、科普、音乐类、菜谱等。
关联媒体内容对应的作者的属性信息可以包括作者权威性、作者影响力等;关联媒体内容与搜索请求之间的相关度用来指示关联媒体内容是否符合用户的搜索需求,相关度越高,表示关联媒体内容越符合用户的搜索需求;关联媒体内容在本次搜索中的排列顺序位可以为对用户的搜索请求在搜索引擎进行搜索,得到的搜索结果中每个关联媒体内容的排列顺序,这里,排序越靠前表明该关联媒体内容越符合用户的搜索需求。
具体的,服务器根据通过步骤S802获取到的关联媒体内容的标识信息,以及存储的每个关联媒体内容的标识信息与提取的核心实体的标识信息之间的对应关系,获取多个核心实体的标识信息;基于上述每个核心实体的标识信息,查找知识图谱,确定每个核心实体的分类信息,基于上述分类信息、以及每个核心实体对应的关联媒体内容的作者的属性信息、每个核心实体对应的关联媒体内容与所述搜索请求之间的相关度、每个核心实体对应的关联媒体内容在本次搜索中的排列顺序位,在上述获取到的多个核心实体的标识信息中,确定目标实体的标识信息。
在具体实施中,在确定目标实体的标识信息之后,可以通过以下方法确定目标实体关联的目标内容信息中的百科知识内容和/或推荐信息,具体描述如下:可以基于目标实体的标识信息,获取与目标实体的标识信息匹配的百科知识内容;和/或,基于目标实体对应的各个关联媒体内容的用户行为数据和/或作者属性信息,确定与目标实体对应的推荐信息。
这里,可以根据目标实体的实体名称、目标实体的实体标识号,在媒体内容库中,获取包含该目标实体的实体名称以及实体标识号信息的百科知识内容。
其中,用户行为数据可以包括用户在浏览关联媒体内容之后的评论内容、搜索内容等;作者属性信息可以包括作者标识信息、作者权威性、作者影响力等。
这里,可以对用户浏览每个目标实体对应的关联媒体内容之后的评论内容和搜索内容进行语义分析,确定用户感兴趣的关联媒体内容,将用户感兴 趣的关联媒体内容作为目标实体的推荐信息。还可以基于每个目标实体对应的各个关联媒体内容的作者标识信息、和作者权威性、以及作者影响力,在上述每个目标实体对应的各个关联媒体内容的作者中,确定作者权威性大于预设权威性阈值和/或作者影响力大于预设影响力阈值的目标作者,在媒体内容库中,将对应该目标作者标识信息的关联媒体内容作为目标实体的推荐信息。
这里,还可以基于每个目标实体对应的各个关联媒体内容的作者标识信息、作者影响力、作者权威性以及用户浏览每个目标实体对应的各个关联媒体内容之后的评论内容和搜索内容,在上述每个目标实体对应的关联媒体内容的作者中,确定作者权威性大于预设权威性阈值和/或作者影响力大于预设影响力阈值的目标作者,在媒体内容库中,将对应该目标作者标识信息且用户感兴趣的关联媒体内容,作为目标实体的推荐信息。
在具体实施中,在确定目标实体的标识信息、百科知识内容和/或推荐信息之后,可以基于目标实体的实体类别,确定目标实体的实体信息中是否包含功能入口信息,具体描述如下:当目标实体的实体类别属于目标实体类别时,则该目标实体的实体信息中包含功能入口信息;当目标实体的实体类别不属于目标实体类别时,则该目标实体的实体信息中包含功能入口信息。
在具体实施中,基于步骤S803确定多个目标实体的标识信息、以及每个目标实体对应的至少一个关联媒体内容、以及每个目标实体的百科知识内容和/或推荐信息、以及每个目标实体的功能入口信息之后,基于步骤S804生成多实体聚合结果。
S804、基于所述多个目标实体的实体信息,生成与搜索请求对应的多实体聚合结果。
在基于步骤S803确定多个目标实体的标识信息、每个目标实体对应的至少一个关联媒体内容、以及每个目标实体的百科知识内容/推荐信息、以及每个目标实体的功能入口信息之后,将每个目标实体的实体信息聚合在一起,生成该搜索请求对应的多实体聚合结果。
本公开实施例提供的搜索结果展示的方法,服务器在接收到用户的搜索请求后,会将符合用户搜索请求的多个目标实体的实体信息聚合在一起,生成多实体聚合结果,并将多实体聚合结果发送给用户端,使用户端将上述多 实体聚合结果展示给用户,用户端可以展示与搜索请求匹配的多个目标实体的实体信息,用户通过实体聚合结果可以直观地看到多个目标实体的实体信息,从而方便了用户进一步筛选感兴趣的目标推荐实体,提高了信息查找效率,节省了搜索时间。
本领域技术人员可以理解,在具体实施方式的上述方法中,各步骤的撰写顺序并不意味着严格的执行顺序而对实施过程构成任何限定,各步骤的具体执行顺序应当以其功能和可能的内在逻辑确定。
基于同一发明构思,本公开实施例中还提供了与搜索结果展示的方法对应的搜索结果展示的装置,由于本公开实施例中的装置解决问题的原理与本公开实施例上述搜索结果展示的方法相似,因此装置的实施可以参见方法的实施,重复之处不再赘述。
实施例三
参照图9所示,为本公开实施例提供的一种搜索结果展示的装置900的示意图,所述装置包括:发送模块901、第一获取模块902、展示模块903;其中,
发送模块901,用于响应搜索触发指令,发送搜索请求;所述搜索请求对应多个实体。
第一获取模块902,用于获取与所述搜索请求对应的多实体聚合结果;其中,所述多实体聚合结果包括与所述搜索请求匹配的多个目标实体的实体信息;所述实体信息是基于所述搜索请求对应的关联媒体内容获取的。
展示模块903,用于展示所述多实体聚合结果。
本公开实施例中,用户在用户端发起搜索请求后,可以得到与搜索请求对应的多实体聚合结果,在该多实体聚合结果中包含多个目标实体的实体信息,这多个目标实体的实体信息为基于搜索请求对应的关联媒体内容获取的,如此,用户端可以直观地向用户展示与搜索请求匹配的多个目标实体的实体信息,用户可以方便地看到其中自己感兴趣的目标实体的实体信息,提高了信息查找效率,节省了搜索时间。
在一种可能的实施方式中,所述实体信息包括目标实体的标识信息和与目标实体关联的目标内容信息;其中,所述目标实体关联的目标内容信息包 含:在与所述搜索请求对应的多个关联媒体内容中,与所述目标实体对应的至少一个关联媒体内容。
在一种可能的实施方式中,展示模块903,具体用于在第一展示区域展示所述多个目标实体的标识信息;确定所述多个目标实体的标识信息中被选中的目标标识信息对应的目标推荐实体;在其它展示区域展示所述目标推荐实体关联的内容信息。
在一种可能的实施方式中,展示模块903,还具体用于根据获取的所述多个目标实体的标识信息,在第一展示区域依次展示所述多个目标实体的标识信息。
在一种可能的实施方式中,展示模块903,还具体用于在第二展示区域依次展示所述目标推荐实体对应的至少一个关联媒体内容。
在一种可能的实施方式中,展示模块903,还具体用于在获取到所述多实体聚合结果后,将在所述第一展示区域的第一个展示位展示的目标实体作为初始的目标推荐实体;若检测到针对所述第一展示区域的其它展示位展示的其它目标实体的标识信息的选中操作,将所述其它目标实体作为更新后的目标推荐实体。
在一种可能的实施方式中,所述目标实体关联的目标内容信息还包含:所述目标实体的百科知识信息和/或推荐信息。
在一种可能的实施方式中,展示模块903,还具体用于在第三展示区域展示所述目标推荐实体的所述百科知识信息和/或推荐信息。
在一种可能的实施方式中,所述目标实体关联的目标内容信息还包含:所述目标推荐实体的功能入口信息;所述功能入口信息用于触发展示所述目标推荐实体对应的消费页面。
在一种可能的实施方式中,展示模块903,还具体用于在第四展示区域展示所述目标推荐实体的功能入口信息;在检测到针对所述功能入口信息的触发操作后,展示所述目标推荐实体对应的消费页面。
在一种可能的实施方式中,展示模块903,还具体用于在所述目标推荐实体的实体类别属于目标实体类别的情况下,在第四展示区域展示所述目标推荐实体的功能入口信息。
实施例四
参照图10所示,为本公开实施例提供的另一种搜索结果展示的装置1000的示意图,所述装置包括:接收模块1001、第二获取模块1002、确定模块1003以及生成模块1004;其中,
接收模块1001,用于接收搜索请求,所述搜索请求对应多个实体。
第二获取模块1002,用于获取与所述搜索请求匹配的关联媒体内容。
确定模块1003,用于根据所述关联媒体内容,确定多个目标实体的实体信息。
生成模块1004,用于基于所述多个目标实体的实体信息,生成与搜索请求对应的多实体聚合结果。
在一种可能的实施方式中,所述实体信息包括目标实体的标识信息和与目标实体关联的目标内容信息;其中,所述目标实体关联的目标内容信息包含:在与所述搜索请求对应的多个关联媒体内容中,与所述目标实体对应的至少一个关联媒体内容。
本公开实施例中,服务器在接收到用户的搜索请求后,会将符合用户搜索请求的多个目标实体的实体信息聚合在一起,生成多实体聚合结果,并将多实体聚合结果发送给用户端,使用户端将上述多实体聚合结果展示给用户,用户端可以展示与搜索请求匹配的多个目标实体的实体信息,用户通过多实体聚合结果可以直观地看到多个目标实体的实体信息,从而方便了用户进一步筛选感兴趣的目标推荐实体,提高了信息查找效率,节省了搜索时间。
在一种可能的实施方式中,所述装置还包括实体提取模块,用于预先对多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息,并存储每个媒体内容的标识信息与提取的核心实体的标识信息之间的对应关系。
确定模块1003,具体用于根据所述关联媒体内容的标识信息,以及存储的所述对应关系,确定目标实体的实体信息。
在一种可能的实施方式中,确定模块1003,还具体用于根据所述关联媒体内容的标识信息,以及存储的所述对应关系,查找与所述关联媒体内容对应的核心实体的标识信息;基于与所述核心实体的标识信息对应的知识图谱信息和所述关联媒体内容,确定查找到的核心实体的属性信息;基于所述搜索请求对应的意图分类信息,和所述核心实体的属性信息,从查找到的核心实体的标识信息中选择目标实体的标识信息。
在一种可能的实施方式中,确定模块1003,还具体用于从知识图谱中查找与所述核心实体的标识信息对应的分类信息;将所述分类信息、所述核心实体对应的关联媒体内容的属性特征、以及所述核心实体在不同关联媒体内容中出现的次数作为所述核心实体属性信息;其中,所述关联媒体内容的属性特征包括:作者的属性信息、所述关联媒体内容与所述搜索请求之间的相关度、所述关联媒体内容在本次搜索中的排列顺序位中的至少一种。
在一种可能的实施方式中,所述实体提取模块,具体用于基于预先训练的实体提取模型对所述多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息;所述实体提取模型为基于人工标注好核心实体的标识信息的媒体内容样本训练得到的。
在一种可能的实施方式中,若所述搜索请求为属性类搜索请求,所述属性类搜索请求是指使用多个属性关键词来表征搜索意图的搜索请求。
第二获取模块1002,具体用于获取与所述搜索请求中的属性关键词匹配的知识图谱类内容;
确定模块1003,还具体用于从与所述搜索请求中的属性关键词匹配的知识图谱类内容中,提取用于展示在所述多实体聚合结果中的所述目标实体的标识信息以及所述目标实体关联的内容信息。
在一种可能的实施方式中,与所述目标实体关联的目标内容信息还包括:百科知识内容和/或推荐信息;所述装置还包括目标内容信息确定模块,用于基于所述目标实体的标识信息,获取与所述目标实体的标识信息匹配的百科知识内容;和/或,基于所述目标实体对应的各个关联媒体内容的用户行为数据和/或作者属性信息,确定与目标实体对应的推荐信息。
关于装置中的各模块的处理流程、以及各模块之间的交互流程的描述可以参照上述方法实施例中的相关说明,这里不再详述。
基于同一技术构思,本申请实施例还提供了一种计算机设备。参照图11所示,为本申请实施例提供的计算机设备1100的结构示意图,包括处理器1101、存储器1102、和总线1103。其中,存储器1102用于存储执行指令,包括内存11021和外部存储器11022;这里的内存11021也称内存储器,用于暂时存放处理器1101中的运算数据,以及与硬盘等外部存储器11022交换的数据,处理器1101通过内存11021与外部存储器11022进行数据交换,当计 算机设备1100运行时,处理器1101与存储器1102之间通过总线1103通信,使得处理器1101执行以下指令:
响应搜索触发指令,发送搜索请求;所述搜索请求对应多个实体;获取与所述搜索请求对应的多实体聚合结果;其中,所述多实体聚合结果包括与所述搜索请求匹配的多个目标实体的实体信息;所述实体信息是基于所述搜索请求对应的关联媒体内容获取的;展示所述多实体聚合结果。
基于同一技术构思,本申请实施例还提供了一种计算机设备。参照图12所示,为本申请实施例提供的计算机设备1200的结构示意图,包括处理器1201、存储器1202、和总线1203。其中,存储器1202用于存储执行指令,包括内存12021和外部存储器12022;这里的内存12021也称内存储器,用于暂时存放处理器1201中的运算数据,以及与硬盘等外部存储器12022交换的数据,处理器1201通过内存12021与外部存储器12022进行数据交换,当计算机设备1200运行时,处理器1201与存储器1202之间通过总线1203通信,使得处理器1201执行以下指令:
接收搜索请求,所述搜索请求对应多个实体;获取与所述搜索请求匹配的关联媒体内容;根据所述关联媒体内容,确定多个目标实体的实体信息;基于所述多个目标实体的实体信息,生成与搜索请求对应的多实体聚合结果。
本公开实施例还提供一种计算机可读存储介质,该计算机可读存储介质上存储有计算机程序,该计算机程序被处理器运行时执行上述方法实施例中所述的搜索结果展示的方法的步骤。其中,该存储介质可以是易失性或非易失的计算机可读取存储介质。
本公开实施例所提供的搜索结果展示的方法的计算机程序产品,包括存储了程序代码的计算机可读存储介质,所述程序代码包括的指令可用于执行上述方法实施例中所述的搜索结果展示的方法的步骤,具体可参见上述方法实施例,在此不再赘述。
本公开实施例还提供一种计算机程序,该计算机程序被处理器执行时实现前述实施例的任意一种方法。该计算机程序产品可以具体通过硬件、软件或其结合的方式实现。在一个可选实施例中,所述计算机程序产品具体体现为计算机存储介质,在另一个可选实施例中,计算机程序产品具体体现为软件产品,例如软件开发包(Software Development Kit,SDK)等等。
所属领域的技术人员可以清楚地了解到,为描述的方便和简洁,上述描述的系统和装置的具体工作过程,可以参考前述方法实施例中的对应过程,在此不再赘述。在本公开所提供的几个实施例中,应该理解到,所揭露的系统、装置和方法,可以通过其它的方式实现。以上所描述的装置实施例仅仅是示意性的,例如,所述单元的划分,仅仅为一种逻辑功能划分,实际实现时可以有另外的划分方式,又例如,多个单元或组件可以结合或者可以集成到另一个系统,或一些特征可以忽略,或不执行。另一点,所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些通信接口,装置或单元的间接耦合或通信连接,可以是电性,机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的,作为单元显示的部件可以是或者也可以不是物理单元,即可以位于一个地方,或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外,在本公开各个实施例中的各功能单元可以集成在一个处理单元中,也可以是各个单元单独物理存在,也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时,可以存储在一个处理器可执行的非易失的计算机可读取存储介质中。基于这样的理解,本公开的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来,该计算机软件产品存储在一个存储介质中,包括若干指令用以使得一台计算机设备(可以是个人计算机,服务器,或者网络设备等)执行本公开各个实施例所述方法的全部或部分步骤。而前述的存储介质包括:U盘、移动硬盘、只读存储器
(Read-Only Memory,ROM)、随机存取存储器(Random Access Memory,RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
最后应说明的是:以上所述实施例,仅为本公开的具体实施方式,用以说明本公开的技术方案,而非对其限制,本公开的保护范围并不局限于此,尽管参照前述实施例对本公开进行了详细的说明,本领域的普通技术人员应当理解:任何熟悉本技术领域的技术人员在本公开揭露的技术范围内,其依然可以对前述实施例所记载的技术方案进行修改或可轻易想到变化,或者对 其中部分技术特征进行等同替换;而这些修改、变化或者替换,并不使相应技术方案的本质脱离本公开实施例技术方案的精神和范围,都应涵盖在本公开的保护范围之内。因此,本公开的保护范围应所述以权利要求的保护范围为准。

Claims (23)

  1. 一种搜索结果展示的方法,其特征在于,包括:
    响应搜索触发指令,发送搜索请求;所述搜索请求对应多个实体;
    获取与所述搜索请求对应的多实体聚合结果;其中,所述多实体聚合结果包括与所述搜索请求匹配的多个目标实体的实体信息;所述实体信息是基于所述搜索请求对应的关联媒体内容获取的;
    展示所述多实体聚合结果。
  2. 根据权利要求1所述的方法,其特征在于,所述实体信息包括目标实体的标识信息和与目标实体关联的目标内容信息;
    其中,所述目标实体关联的目标内容信息包含:在与所述搜索请求对应的多个关联媒体内容中,与所述目标实体对应的至少一个关联媒体内容。
  3. 根据权利要求2所述的方法,其特征在于,展示所述多实体聚合结果,包括:
    在第一展示区域展示所述多个目标实体的标识信息;
    确定所述多个目标实体的标识信息中被选中的目标标识信息对应的目标推荐实体;
    在其它展示区域展示所述目标推荐实体关联的内容信息。
  4. 根据权利要求3所述的方法,其特征在于,在第一展示区域展示所述多个目标实体的标识信息,包括:
    根据获取的所述多个目标实体的标识信息,在第一展示区域依次展示所述多个目标实体的标识信息。
  5. 根据权利要求3所述的方法,其特征在于,展示所述多实体聚合结果,包括:
    在第二展示区域依次展示所述目标推荐实体对应的至少一个关联媒体内容。
  6. 根据权利要求3所述的方法,其特征在于,所述确定所述多个目标实体的标识信息中被选中的目标标识信息对应的目标推荐实体,包括:
    在获取到所述多实体聚合结果后,将在所述第一展示区域的第一个展示位展示的目标实体作为初始的目标推荐实体;
    若检测到针对所述第一展示区域的其它展示位展示的其它目标实体的标识信息的选中操作,将所述其它目标实体作为更新后的目标推荐实体。
  7. 根据权利要求2所述的方法,其特征在于,所述目标实体关联的目标内容信息还包含:所述目标实体的百科知识信息和/或推荐信息。
  8. 根据权利要求7所述的方法,其特征在于,展示所述多实体聚合结果,包括:
    在第三展示区域展示目标推荐实体的所述百科知识信息和/或推荐信息。
  9. 根据权利要求2所述的方法,其特征在于,所述目标实体关联的目标内容信息还包含:目标推荐实体的功能入口信息;所述功能入口信息用于触发展示所述目标推荐实体对应的消费页面。
  10. 根据权利要求9所述的方法,其特征在于,展示所述多实体聚合结果,包括:
    在第四展示区域展示所述目标推荐实体的功能入口信息;
    在检测到针对所述功能入口信息的触发操作后,展示所述目标推荐实体对应的消费页面。
  11. 根据权利要求10所述的方法,其特征在于,在第四展示区域展示所述目标推荐实体的功能入口信息,包括:
    在所述目标推荐实体的实体类别属于目标实体类别的情况下,在第四展示区域展示所述目标推荐实体的功能入口信息。
  12. 一种搜索结果展示的方法,其特征在于,包括:
    接收搜索请求,所述搜索请求对应多个实体;
    获取与所述搜索请求匹配的关联媒体内容;
    根据所述关联媒体内容,确定多个目标实体的实体信息;
    基于所述多个目标实体的实体信息,生成与搜索请求对应的多实体聚合结果。
  13. 根据权利要求12所述的方法,其特征在于,所述实体信息包括目标实体的标识信息和与目标实体关联的目标内容信息;
    其中,所述目标实体关联的目标内容信息包含:在与所述搜索请求对应的多个关联媒体内容中,与所述目标实体对应的至少一个关联媒体内容。
  14. 根据权利要求13所述的方法,其特征在于,所述方法还包括:
    预先对多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息,并存储每个媒体内容的标识信息与提取的核心实体的标识信息之间的对应关系;
    所述根据所述关联媒体内容,确定目标实体的实体信息,包括:
    根据所述关联媒体内容的标识信息,以及存储的所述对应关系,确定目标实体的实体信息。
  15. 根据权利要求14所述的方法,其特征在于,根据所述关联媒体内容的标识信息,以及存储的所述对应关系,确定目标实体的实体信息,包括:
    根据所述关联媒体内容的标识信息,以及存储的所述对应关系,查找与所述关联媒体内容对应的核心实体的标识信息;
    基于与所述核心实体的标识信息对应的知识图谱信息和所述关联媒体内容,确定查找到的核心实体的属性信息;
    基于所述搜索请求对应的意图分类信息,和所述核心实体的属性信息,从查找到的核心实体的标识信息中选择目标实体的标识信息。
  16. 根据权利要求15所述的方法,其特征在于,基于与所述核心实体的标识信息对应的知识图谱信息和所述关联媒体内容,确定查找到的核心实体的属性信息,包括:
    从知识图谱中查找与所述核心实体的标识信息对应的分类信息;
    将所述分类信息、所述核心实体对应的关联媒体内容的属性特征、以及所述核心实体在不同关联媒体内容中出现的次数作为所述核心实体属性信息;
    其中,所述关联媒体内容的属性特征包括:作者的属性信息、所述关联媒体内容与所述搜索请求之间的相关度、所述关联媒体内容在本次搜索中的排列顺序位中的至少一种。
  17. 根据权利要求14所述的方法,其特征在于,所述预先对多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息,包括:
    基于预先训练的实体提取模型对所述多个媒体内容进行实体提取,得到提取的多个核心实体的标识信息;所述实体提取模型为基于人工标注好核心实体的标识信息的媒体内容样本训练得到的。
  18. 根据权利要求13所述的方法,其特征在于,若所述搜索请求为属性类搜索请求,所述属性类搜索请求是指使用多个属性关键词来表征搜索意图的搜索请求,所述获取与所述搜索请求匹配的关联媒体内容,包括:
    获取与所述搜索请求中的属性关键词匹配的知识图谱类内容;
    所述根据所述关联媒体内容,确定所述目标实体的标识信息以及与所述目标实体关联的内容信息,包括:
    从与所述搜索请求中的属性关键词匹配的知识图谱类内容中,提取用于展示在所述多实体聚合结果中的所述目标实体的标识信息以及所述目标实体关联的内容信息。
  19. 根据权利要求13所述的方法,其特征在于,与所述目标实体关联的目标内容信息还包括:百科知识内容和/或推荐信息;
    根据以下步骤确定所述百科知识内容和/或推荐信息:
    基于所述目标实体的标识信息,获取与所述目标实体的标识信息匹配的百科知识内容;和/或,
    基于所述目标实体对应的各个关联媒体内容的用户行为数据和/或作者属性信息,确定与目标实体对应的推荐信息。
  20. 一种搜索结果展示的装置,其特征在于,包括:
    发送模块,用于响应搜索触发指令,发送搜索请求;所述搜索请求对应多个实体;
    第一获取模块,用于获取与所述搜索请求对应的多实体聚合结果;其中,所述多实体聚合结果包括与所述搜索请求匹配的多个目标实体的实体信息;所述实体信息是基于所述搜索请求对应的关联媒体内容获取的;
    展示模块,用于展示所述多实体聚合结果。
  21. 一种搜索结果展示的装置,其特征在于,包括:
    接收模块,用于接收搜索请求,所述搜索请求对应多个实体;
    第二获取模块,用于获取与所述搜索请求匹配的关联媒体内容;
    确定模块,用于根据所述关联媒体内容,确定多个目标实体的实体信息;
    生成模块,用于基于所述多个目标实体的实体信息,生成与搜索请求对应的多实体聚合结果。
  22. 一种计算机设备,其特征在于,包括:处理器、存储器和总线,所述存储器存储有所述处理器可执行的机器可读指令,当计算机设备运行时,所述处理器与所述存储器之间通过总线通信,所述机器可读指令被所述处理器执行时执行如权利要求1至11任一所述的搜索结果展示的方法的步骤,或执行如权利要求12至19任一所述的搜索结果展示的方法的步骤。
  23. 一种计算机可读存储介质,其特征在于,该计算机可读存储介质上存储有计算机程序,该计算机程序被处理器运行时执行如权利要求1至11或任一所述的搜索结果展示的方法的步骤,或执行如权利要求12至19任一项所述的搜索结果展示的方法的步骤。
PCT/CN2021/109325 2020-09-04 2021-07-29 一种搜索结果展示的方法、装置及计算机存储介质 Ceased WO2022048360A1 (zh)

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