WO2020042376A1 - 用于输出信息的方法和装置 - Google Patents

用于输出信息的方法和装置 Download PDF

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Publication number
WO2020042376A1
WO2020042376A1 PCT/CN2018/115949 CN2018115949W WO2020042376A1 WO 2020042376 A1 WO2020042376 A1 WO 2020042376A1 CN 2018115949 W CN2018115949 W CN 2018115949W WO 2020042376 A1 WO2020042376 A1 WO 2020042376A1
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target entity
video
data
information
entity
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PCT/CN2018/115949
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English (en)
French (fr)
Inventor
陈大伟
刘宝
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北京字节跳动网络技术有限公司
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Publication of WO2020042376A1 publication Critical patent/WO2020042376A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/36—Creation of semantic tools, e.g. ontology or thesauri

Definitions

  • the embodiments of the present application relate to the field of computer technology, and in particular, to a method and an apparatus for outputting information.
  • Knowledge graph is a kind of knowledge base called semantic network, that is, a knowledge base with a directed graph structure, where the nodes of the graph represent entities or concepts, and the edges of the graph Represents various semantic relationships between entities / concepts.
  • the knowledge map can be applied to various fields, such as information search, information recommendation, and other fields. By using the knowledge map, other entities associated with an entity characterizing certain information can be obtained, so that other information associated with the information can be obtained more accurately.
  • the embodiments of the present application provide a method and a device for outputting information.
  • an embodiment of the present application provides a method for outputting information.
  • the method includes: determining at least one target entity from an entity included in a pre-established knowledge map that characterizes a video; and for at least one target entity, The target entity determines at least one popularity data from the attribute information of the target entity, wherein the popularity data is used to characterize the degree of attention of the video characterized by the target entity; based on the determined at least one popularity data, the video characterized by the target entity Perform scoring; sort at least one target entity according to the obtained score, and output related information of the target entity in the at least one target entity according to the ranking.
  • scoring the video characterized by the target entity based on the determined at least one heat data includes: for the heat data in the determined at least one heat data, based on a preset, corresponding to the heat data Conversion method to obtain the score corresponding to the heat data; based on a preset weight value corresponding to the heat data, weight the sum of the determined scores to obtain the score of the video represented by the target entity.
  • the method before the at least one target entity is sorted according to the size of the obtained score, the method further includes: for the target entity in the at least one target entity, obtaining a preset video representing the target entity. Information about the cost of permissions.
  • outputting related information of the target entity in the at least one target entity according to the order includes: outputting related information of the target entity in the at least one target entity and a video of the target entity characterization in the at least one target entity in the order. Information about the cost of permissions.
  • the popularity data includes at least one of the following: playback volume data of a video represented by a target entity, attention data of a video represented by a target entity, and comment volume data of a video represented by a target entity.
  • the related information of the target entity includes at least one of the following: a title of a video represented by the target entity, an image included in the video represented by the target entity, and heat data corresponding to the target entity.
  • an embodiment of the present application provides an apparatus for outputting information.
  • the apparatus includes: a determining unit configured to determine at least one target entity from a pre-established knowledge map that includes a video characterization entity; a score; A unit configured to determine, for at least one target entity, at least one popularity data from attribute information of the target entity, wherein the popularity data is used to represent a degree of attention of a video characterized by the target entity; based on the determined At least one popularity data, scoring the video characterized by the target entity; an output unit configured to sort at least one target entity according to the size of the obtained score, and output the target entity of the at least one target entity according to the ranking Related Information.
  • the scoring unit includes a conversion module configured to obtain a score corresponding to the heat data based on a preset conversion method corresponding to the heat data for the heat data in the determined at least one heat data.
  • a calculation module configured to perform a weighted summation on the determined scores based on a preset weight value corresponding to the heat data to obtain a score of a video characterized by the target entity.
  • the apparatus further includes: an obtaining unit configured to obtain, for a target entity in the at least one target entity, preset rights and cost information of a video represented by the target entity.
  • the output unit is further configured to output, in order, related information of the target entity in the at least one target entity and rights and cost information of the video characterized by the target entity in the at least one target entity.
  • the popularity data includes at least one of the following: playback volume data of a video represented by a target entity, attention data of a video represented by a target entity, and comment volume data of a video represented by a target entity.
  • the related information of the target entity includes at least one of the following: a title of a video represented by the target entity, an image included in the video represented by the target entity, and heat data corresponding to the target entity.
  • an embodiment of the present application provides a server.
  • the server includes: one or more processors; a storage device on which one or more programs are stored; and when one or more programs are processed by one or more The processor executes such that one or more processors implement the method as described in any implementation of the first aspect.
  • an embodiment of the present application provides a computer-readable medium having stored thereon a computer program that, when executed by a processor, implements the method as described in any implementation manner of the first aspect.
  • the method and device for outputting information determine the at least one target entity from the entities that are included in the knowledge map that characterizes the video, and then determine the heat data of each target entity, and based on the heat data, Scoring the video represented by each target entity, and finally sorting each target entity according to the score size and outputting related information of the target entity in at least one target entity according to the order, so that the attribute information of the entity in the knowledge map can be effectively used , Improve the accuracy of sorting the identified target entities, and help to show users relevant information about each target entity.
  • FIG. 1 is an exemplary system architecture diagram to which an embodiment of the present application can be applied;
  • FIG. 1 is an exemplary system architecture diagram to which an embodiment of the present application can be applied;
  • FIG. 2 is a flowchart of an embodiment of a method for outputting information according to an embodiment of the present application
  • FIG. 3 is a schematic diagram of an application scenario of a method for outputting information according to an embodiment of the present application
  • FIG. 5 is a schematic structural diagram of an embodiment of an apparatus for outputting information according to an embodiment of the present application
  • FIG. 6 is a schematic structural diagram of a computer system suitable for implementing a server according to an embodiment of the present application.
  • FIG. 1 illustrates an exemplary system architecture 100 to which a method for outputting information or a device for outputting information of an embodiment of the present application can be applied.
  • the system architecture 100 may include terminal devices 101, 102, and 103, a network 104, and a server 105.
  • the network 104 is a medium for providing a communication link between the terminal devices 101, 102, 103 and the server 105.
  • the network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, and so on.
  • the user can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages and the like.
  • Various communication client applications can be installed on the terminal devices 101, 102, and 103, such as video playback applications, web browser applications, search applications, instant communication tools, and social platform software.
  • the terminal devices 101, 102, and 103 may be hardware or software.
  • the terminal devices 101, 102, and 103 can be various electronic devices, including but not limited to smartphones, tablets, e-book readers, MP3 players (Moving Pictures Experts Group Audio Layer III, Motion Picture Expert Compression Standard Audio Level 3), MP4 (Moving Picture Experts Group Audio Audio Layer IV, Motion Picture Expert Compression Standard Audio Level 4) player, laptop portable computer and desktop computer, etc.
  • the terminal devices 101, 102, and 103 are software, they can be installed in the electronic devices listed above. It can be implemented as multiple software or software modules (such as software or software modules used to provide distributed services), or it can be implemented as a single software or software module. It is not specifically limited here.
  • the server 105 may be a server that provides various services, such as a background information processing server that provides support for related information of the target entity displayed on the terminal devices 101, 102, and 103.
  • the background information processing server may process the entities included in the pre-established knowledge map and obtain the processing results (for example, related information of the sorted target entity).
  • the method for outputting information provided by the embodiment of the present application is generally executed by the server 105, and accordingly, the device for outputting information is generally set in the server 105.
  • the server may be hardware or software.
  • the server can be implemented as a distributed server cluster consisting of multiple servers or as a single server.
  • the server can be implemented as multiple software or software modules (such as software or software modules used to provide distributed services), or it can be implemented as a single software or software module. It is not specifically limited here.
  • terminal devices, networks, and servers in FIG. 1 are merely exemplary. According to implementation needs, there can be any number of terminal devices, networks, and servers.
  • the method for outputting information includes the following steps:
  • Step 201 Determine at least one target entity from entities included in a pre-established knowledge map that characterize a video.
  • an execution subject (for example, a server shown in FIG. 1) of a method for outputting information may determine at least one target entity from entities included in a pre-established knowledge map and representing a video. Among them, the target entity is used to characterize the video.
  • the pre-established knowledge map may be stored in the execution subject, or may be stored in other electronic devices in communication with the execution subject.
  • the entities in the knowledge map can be used to characterize a certain thing or concept (such as characterizing people, places, times, information, etc.).
  • the form of the entity may include at least one of the following: numbers, characters, symbols, and so on.
  • the knowledge map may include an entity for characterizing a video.
  • the pre-established entity used to characterize a video may be “v-abc”, where “v” indicates that the entity is used to characterize a video, and “abc” is an identifier used to characterize the video.
  • the knowledge map of this embodiment may also include entities used to characterize things or concepts other than video. For example, a pre-established entity used to characterize a person may be "p-xyz", where "p” indicates that the entity is used to characterize a character, and "xyz” is an identifier used to characterize the character.
  • the entity representing the video may have corresponding attribute information.
  • Attribute information is information related to the video represented by the entity, and may include, but is not limited to, at least one of the following: information about people (such as video producers, actors, directors, etc.) related to the video, time (such as showtime, Shooting time, etc.), the source information of the video (such as the playback address of the video, the name of the website where the video is located, etc.), and other information related to the video content (such as the video profile, stills, poster pictures, etc.).
  • the correspondence between the entity and the attribute information can be represented by a data structure in the form of a triple, namely, “entity-attribute-attribute value”, wherein the attribute information of the entity can include the above-mentioned attribute-attribute value.
  • a triple may be "abc123-name-XXX", where "abc123” is an entity used to characterize the movie "XXX”, "name” is an attribute, and "XXX" is an attribute value.
  • the above-mentioned execution subject may determine at least one target entity from the entities included in the pre-established knowledge graph and representing the video according to various methods.
  • the above-mentioned execution body may match a search term input by a technician in advance with text information included in attribute information of each entity representing a video, and determine an entity corresponding to the text information including the search term as a target entity.
  • the entity may have identification information, and the execution entity may determine the target entity according to the identification information specified by the technician.
  • the video represented by each target entity in the determined at least one target entity may have some of the same attributes (e.g., the represented video is of the same type, the main character of the represented video is the same person, and the represented video comes from the same website Etc.) entities.
  • Step 202 For at least one target entity, determine at least one popularity data from the attribute information of the target entity; and based on the determined at least one popularity data, score a video characterized by the target entity.
  • the execution entity may perform the following steps:
  • Step 2021 Determine at least one popularity data from the attribute information of the target entity.
  • the heat data is used to represent the degree of attention of the video represented by the target entity.
  • the popularity data can be numerical values, such as the number of playbacks and clicks. When the popularity data is a numerical value, the higher the numerical value, the higher the degree of attention that characterizes the video.
  • the popularity data may also be other non-numerical data, such as information characterizing the user's evaluation of the quality of the video (such as "praise”, “medium rating”, “bad rating”, etc.).
  • the popularity data may include, but is not limited to, at least one of the following: video playback data of the target entity representation, video attention volume data of the target entity representation video, and video of the target entity representation Review volume data, etc.
  • the popularity data may be obtained in various ways.
  • the play volume data may be a web address included by the execution entity according to the attribute information of the target entity, and the playback volume data of the video represented by the target entity obtained from the web page indicated by the URL.
  • the playback volume data may be the actual playback volume within a preset time period (for example, the last day), or the actual playback volume within the preset time period and the total playback volume of the video included on the website where the URL is located Ratio.
  • the amount of attention data may be the number of users recorded on the website, following or bookmarking or clicking on the video represented by the target entity.
  • the amount of comment data may be the number of comments on videos characterized by the target entity on the website.
  • the attribute information of the target entity may include at least one website address.
  • the type of popularity data may be obtained by the execution entity from web pages indicated by the respective websites. Sum of heat data.
  • Step 2022 Based on the determined at least one degree of heat data, score a video characterized by the target entity.
  • the score can be used to represent the degree of attention of the video represented by the target entity.
  • the higher the score the higher the degree of attention of the video identified by the target entity.
  • the execution entity may add the respective values, and determine a result obtained by the addition as a score value of the target entity.
  • the above-mentioned execution body may score the video characterized by the target entity according to the following steps:
  • a score corresponding to the heat data is obtained.
  • the conversion modes corresponding to the respective heat data may be the same or different.
  • the heat data when the heat data is a numerical value, the heat data can be proportionally converted into a preset value range.
  • the preset value range is [0,1]
  • a certain popularity data is the playback volume of the video of the day.
  • the score corresponding to this popularity data may be the ratio of the playback volume to the preset maximum playback volume. When the ratio is greater than 1, The score is determined as 1 point.
  • the non-numeric data can be converted into a score within a preset numerical range.
  • the rating may be mapped to a value range [0,1] according to a preset rule (for example, 1 point for positive reviews, 0.5 point for medium ratings, and 0 for poor ratings). Minute).
  • each of the heat data may correspond to a preset weight value, and the heat data with a large weight value has a greater degree of contribution to the score of the obtained video characterized by the target entity.
  • at least one popularity data includes the amount of playback, the amount of attention, the amount of comments, and the corresponding weight values are 0.6, 0.2, 0.2 respectively, then the video represented by the target entity has a rating of 0.6 ⁇ playback amount + 0.2 ⁇ attention amount + 0.2 ⁇ comment the amount.
  • Step 203 Sort at least one target entity according to the obtained score, and output related information of the target entity in the at least one target entity according to the ranking.
  • the execution entity may sort at least one target entity according to the size of each score obtained in step 202, and output related information of the target entity in the at least one target entity according to the ranking.
  • the related information may be information included in the attribute information of the target entity, or may be other information related to the target entity (for example, the serial number of the target entity after ordering).
  • the attribute information may include various types of sub-information, and the sub-information may have a corresponding identification or serial number to distinguish the type of the molecular information.
  • the execution subject may extract sub-information of a preset category from the attribute information as related information.
  • the output related information of the sorted target entity can more specifically show the target entity, which helps the user to view the video of the target entity's representation according to the order of the related information.
  • the related information of the target entity may include, but is not limited to, at least one of the following: the title of the video represented by the target entity, and the image included in the video represented by the target entity (such as video screenshots, stills) , Poster images, etc.), and popularity data (such as playback volume, attention volume, etc.) corresponding to the target entity.
  • the execution body may output related information of the target entity in various ways.
  • the related information of the target entity is displayed on a display connected to the execution subject, or the related information of the target entity is output to a terminal device (such as the terminal device shown in FIG. 1) that is communicatively connected with the execution subject.
  • FIG. 3 is a schematic diagram of an application scenario of a method for outputting information according to this embodiment.
  • the server 301 first determines three target entities 303, 304, and 305 from the entities included in the pre-established knowledge map 302 and representing the video.
  • the target entities 303, 304, and 305 are entities searched by the server 301 based on the search term "starring Lee XX movie" input by the technician, among the entities that represent the video included in the knowledge map 302, that is, the three target entities are used respectively Yu characterizes the movie starring Li XX.
  • the server 301 determines, from the attribute information of each target entity, the amount of playback of the video represented by the target entity on the website to which it belongs on the same day as the heat data, that is, 3031 (corresponding to “200,000”) and 3041 (corresponding to Playback volume "180,000"), 3051 (corresponding playback volume "100,000”). Subsequently, the server 301 divides the actual value of the playback amount by 10,000 to obtain the respective scores 3032 (ie, "20"), 3042 (ie, "18"), and 3052 (ie, "10") of the target entities 303, 304, and 305.
  • the server sorts the target entities 303, 304, and 305 in the order of the obtained scores, and outputs related information of the sorted target entities to a display 306 connected to the server 301 for display. For example, on the display 306, the movie name "XXX” and the play volume "200,000" represented by the target entity 303 are displayed, the movie name "YYY” and the play volume "180,000” represented by the target entity 304 are displayed, and the movie represented by the target entity 305 is displayed Name "ZZZ" and play volume "100,000".
  • the method provided by the foregoing embodiments of the present application determines at least one target entity from entities that are included in a pre-established knowledge map and that characterize a video, and then determines heat data of each target entity, and characterizes each target entity based on the heat data.
  • the video is scored, and finally each target entity is sorted according to the size of the score, and the relevant information of the target entity in at least one target entity is output according to the ranking, so that the attribute information of the entity in the knowledge map can be effectively used to improve the determination of the
  • the accuracy of the sorting of the target entities helps to show users the relevant information of each target entity in a targeted manner.
  • FIG. 4 a flowchart 400 of yet another embodiment of a method for outputting information is shown.
  • the process 400 of the method for outputting information includes the following steps:
  • Step 401 Determine at least one target entity from the entities included in the pre-established knowledge map and representing the video.
  • step 401 is substantially the same as step 201 in the embodiment corresponding to FIG. 2, and details are not described herein again.
  • Step 402 For at least one target entity, determine at least one popularity data from the attribute information of the target entity; and based on the determined at least one popularity data, score a video characterized by the target entity.
  • step 402 is substantially the same as step 202 in the embodiment corresponding to FIG. 2, and details are not described herein again.
  • Step 403 For at least one target entity, obtain preset rights and cost information of the video represented by the target entity.
  • an execution subject for example, a server shown in FIG. 1
  • a server shown in FIG. 1 can obtain preset rights and cost information of a video represented by the target entity.
  • the right cost information can be used to characterize the price to be paid by the user to obtain the playback right of the video represented by the target entity.
  • the right cost information can be numeric or other non-numeric data.
  • the rights cost information may be a copyright price value of a video characterized by a target entity. Or it is calculated based on the copyright price of the video represented by the target entity, and represents the price paid by the user.
  • the right price information when the ratio of the copyright price of video A to the daily playback volume of video A represented by a target entity is greater than the first preset value, the right price information may be text information "high"; when the copyright price of video A and video When the ratio of the single-day play volume of A is less than or equal to the first preset value and greater than or equal to the second preset value, the right price information may be text information “medium”; when the copyright price of video A and the daily play volume of video A When the ratio is smaller than the second preset value, the permission cost information may be text information “low”.
  • Step 404 Sort at least one target entity according to the obtained score, and output related information of the target entity in the at least one target entity and the rights cost of the video characterized by the target entity in the at least one target entity according to the ranking. information.
  • the execution entity may first sort at least one target entity according to the obtained score, and according to the ranking, output related information of the target entity in the at least one target entity and the information in the at least one target entity. Information about the rights cost of the video represented by the target entity.
  • the method for sorting at least one target entity in this step is basically the same as the method for sorting at least one target entity described in step 203 in the corresponding embodiment of FIG. 2, and the description of related information of the target entity may be Referring to step 203 in the embodiment corresponding to FIG. 2, details are not described herein again.
  • the related information of the target entity and the permission cost information of the video represented by the target entity may be output to a display connected to the above-mentioned execution entity; or the related information of the target entity and the rights of the video represented by the target entity may be output.
  • the cost information is output to a terminal device (such as the terminal device shown in FIG. 1) that is communicatively connected to the execution subject. Thereby, it is possible to show the user the related information of the target entity and the rights cost information of the video represented by the target entity. It helps to present more information to users in a more targeted manner.
  • the process 400 of the method for outputting information in this embodiment highlights the rights and costs of obtaining the video represented by the target entity and the authority to output the target entity. Steps in cost information. Therefore, the solution described in this embodiment can output more information, which helps to show the user the rights and cost information of the video represented by the target entity, thereby further improving the pertinence of the information displayed to the user.
  • this application provides an embodiment of a device for outputting information.
  • the device embodiment corresponds to the method embodiment shown in FIG. 2.
  • the device can be specifically applied to various electronic devices.
  • the apparatus 500 for outputting information in this embodiment includes: a determining unit 501 configured to determine at least one target entity from entities representing video included in a pre-established knowledge map; a scoring unit 502, Configured to determine, for at least one target entity, at least one popularity data from attribute information of the target entity, wherein the popularity data is used to characterize a degree of attention of a video represented by the target entity; based on the determined at least one Heat data to score the video characterized by the target entity; an output unit 503 is configured to sort at least one target entity according to the size of the obtained score, and output the correlation of the target entity in the at least one target entity according to the ranking information.
  • the determining unit 501 may determine at least one target entity from entities included in a pre-established knowledge map that characterize a video. Among them, the target entity is used to characterize the video.
  • the pre-established knowledge map may be stored in the device 500, or may be stored in another electronic device that is communicatively connected with the device 500.
  • the entities in the knowledge map can be used to characterize a certain thing or concept (such as characterizing people, places, times, information, etc.).
  • the form of the entity may include at least one of the following: numbers, characters, symbols, and so on.
  • the knowledge map may include an entity for characterizing a video.
  • the pre-established entity used to characterize a video may be “v-abc”, where “v” indicates that the entity is used to characterize a video, and “abc” is an identifier used to characterize the video.
  • the knowledge map of this embodiment may also include entities used to characterize things or concepts other than video. For example, a pre-established entity used to characterize a person may be "p-xyz", where "p” indicates that the entity is used to characterize a character, and "xyz” is an identifier used to characterize the character.
  • the entity representing the video may have corresponding attribute information.
  • the attribute information may be information related to the video represented by the entity, and may include, but is not limited to, at least one of the following: information about a person (such as a video producer, an actor, a director, etc.) related to the video, and a time (such as a release time) related to the video , Shooting time, etc.), the source information of the video (such as the video's playback address, the name of the website where the video is located, etc.), and other information related to the video content (such as the video profile, stills, poster pictures, etc.).
  • the correspondence between the entity and the attribute information can be represented by a data structure in the form of a triple, namely, “entity-attribute-attribute value”, wherein the attribute information of the entity can include the above-mentioned attribute-attribute value.
  • a triple may be "abc123-name-XXX", where "abc123” is an entity used to characterize the movie "XXX”, "name” is an attribute, and "XXX" is an attribute value.
  • the above-mentioned determining unit 501 may determine at least one target entity from various entities included in the pre-established knowledge map that characterize the video according to various methods.
  • the foregoing determining unit 501 may match a search term input by a technician with text information included in attribute information of each entity characterizing a video, and determine an entity corresponding to the text information including the search term as a target entity.
  • the entity may have identification information, and the determining unit 501 may determine the target entity according to the identification information specified by the technician.
  • the video represented by each target entity in the determined at least one target entity may have some of the same attributes (e.g., the represented video is of the same type, the main character of the represented video is the same person, and the represented video comes from the same website Etc.) entities.
  • the following steps may be performed for the target entity scoring unit 502 in the at least one target entity:
  • At least one heat data is determined from the attribute information of the target entity.
  • the heat data is used to represent the degree of attention of the video represented by the target entity.
  • the heat data may be a numerical value, such as a playback amount, a click amount, and the like.
  • the popularity data may also be other non-numerical data, such as information characterizing the user's evaluation of the quality of the video (such as "praise”, “medium rating”, “bad rating”, etc.).
  • the heat data is a numerical value, the higher the numerical value, the higher the degree of attention that characterizes the video.
  • a video characterized by the target entity is scored.
  • the above-mentioned scoring unit 502 may add the respective values, and determine a result obtained by the addition as a score value of the target entity.
  • the output unit 503 may sort at least one target entity according to the size of each score obtained by the scoring unit 502, and output related information of the target entity in the at least one target entity according to the ranking.
  • the related information may be information included in the attribute information of the target entity, or may be other information related to the target entity (for example, the serial number of the target entity after ordering).
  • the attribute information may include various types of sub-information, and the sub-information may have a corresponding identification or serial number to distinguish the type of the molecular information.
  • the output unit 503 may extract sub-information of a preset category from the attribute information as related information.
  • the output related information of the sorted target entity can more specifically show the target entity, which helps the user to view the video of the target entity's representation according to the order of the related information.
  • the scoring unit 502 may include: a conversion module (not shown in the figure), configured to, for the heat data in the determined at least one heat data, based on a preset, A conversion method corresponding to the heat data to obtain a score corresponding to the heat data; a calculation module (not shown in the figure) is configured to weight the determined scores based on a preset weight value corresponding to the heat data Sum to get the score of the video represented by the target entity.
  • the apparatus 500 may further include: an obtaining unit (not shown in the figure) configured to obtain a preset, target for a target entity among at least one target entity. Information about the rights cost of the video represented by the entity.
  • the output unit 503 may be further configured to output, in order, the related information of the target entity in the at least one target entity and the video of the video characterized by the target entity in the at least one target entity. Rights cost information.
  • the popularity data may include at least one of the following: video playback data of the target entity, video attention data of the target entity, and video comment volume of the target entity. data.
  • the related information of the target entity may include at least one of the following: a title of a video represented by the target entity, an image included in the video represented by the target entity, and heat data corresponding to the target entity.
  • the apparatus provided by the foregoing embodiment of the present application determines an at least one target entity from the entities representing video that are included in a pre-established knowledge map, and then determines heat data of each target entity, and characterizes each target entity based on the heat data.
  • the video is scored, and finally each target entity is sorted according to the size of the score, and the relevant information of the target entity in at least one target entity is output according to the ranking, so that the attribute information of the entity in the knowledge map can be effectively used to improve the determination of the
  • the accuracy of the sorting of the target entities helps to show users the relevant information of each target entity in a targeted manner.
  • FIG. 6 shows a schematic structural diagram of a computer system 600 suitable for implementing a server according to an embodiment of the present application.
  • the server shown in FIG. 6 is only an example, and should not impose any limitation on the functions and scope of use of the embodiments of the present application.
  • the computer system 600 includes a central processing unit (CPU) 601, which can be loaded into a random access memory (RAM) 603 according to a program stored in a read-only memory (ROM) 602 or from a storage portion 608. Instead, perform various appropriate actions and processes.
  • RAM random access memory
  • ROM read-only memory
  • various programs and data required for the operation of the system 600 are also stored.
  • the CPU 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604.
  • An input / output (I / O) interface 605 is also connected to the bus 604.
  • the following components are connected to the I / O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), and the speaker; a storage portion 608 including a hard disk and the like; a communication section 609 including a network interface card such as a LAN card, a modem, and the like.
  • the communication section 609 performs communication processing via a network such as the Internet.
  • the driver 610 is also connected to the I / O interface 605 as necessary.
  • a removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 610 as needed, so that a computer program read therefrom is installed into the storage section 608 as needed.
  • the process described above with reference to the flowchart may be implemented as a computer software program.
  • embodiments of the present disclosure include a computer program product including a computer program carried on a computer-readable medium, the computer program containing program code for performing a method shown in a flowchart.
  • the computer program may be downloaded and installed from a network through the communication portion 609, and / or installed from a removable medium 611.
  • CPU central processing unit
  • the computer-readable medium described in this application may be a computer-readable signal medium or a computer-readable medium or any combination of the foregoing.
  • the computer-readable medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable Read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the foregoing.
  • a computer-readable medium may be any tangible medium that contains or stores a program that can be used by or in combination with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a data signal that is included in baseband or propagated as part of a carrier wave, and which carries computer-readable program code. Such a propagated data signal may take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • the computer-readable signal medium can also be any computer-readable medium other than a computer-readable medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device.
  • Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
  • Computer program code for performing the operations of the present application may be written in one or more programming languages, or combinations thereof, including programming languages such as Java, Smalltalk, C ++, and also conventional Procedural programming language—such as "C" or a similar programming language.
  • the program code can be executed entirely on the user's computer, partly on the user's computer, as an independent software package, partly on the user's computer, partly on a remote computer, or entirely on a remote computer or server.
  • the remote computer can be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (such as through an Internet service provider) Internet connection).
  • LAN local area network
  • WAN wide area network
  • Internet service provider Internet service provider
  • each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, which contains one or more functions to implement a specified logical function Executable instructions.
  • the functions noted in the blocks may also occur in a different order than those marked in the drawings. For example, two successively represented boxes may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved.
  • each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts can be implemented by a dedicated hardware-based system that performs the specified function or operation , Or it can be implemented with a combination of dedicated hardware and computer instructions.
  • the units described in the embodiments of the present application may be implemented by software or hardware.
  • the described unit may also be provided in a processor, for example, it may be described as: a processor includes a determining unit, a scoring unit, and an output unit. Among them, the names of these units do not constitute a definition of the unit itself in some cases.
  • the determining unit may also be described as "identifying at least one target entity from the entities included in the pre-established knowledge map that characterize the video Unit. "
  • the present application also provides a computer-readable medium, which may be included in the server described in the above embodiments; or may exist alone without being assembled into the server.
  • the above computer-readable medium carries one or more programs, and when the one or more programs are executed by the server, the server is caused to: determine at least one target entity from entities included in a pre-established knowledge map that characterize video; For at least one target entity, determine at least one popularity data from the attribute information of the target entity, wherein the popularity data is used to characterize the degree of attention of the video represented by the target entity; based on the determined at least one popularity data, The video characterized by the target entity is scored; at least one target entity is sorted according to the magnitude of the obtained score; and related information of the target entity in the at least one target entity is output according to the ranking.

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Abstract

一种用于输出信息的方法和装置。该方法包括：从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体（201）；对于至少一个目标实体中的目标实体，从该目标实体的属性信息中确定至少一个热度数据，其中，热度数据用于表征目标实体表征的视频的被关注程度；基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分（202）；按照所得到的评分的大小，对至少一个目标实体进行排序，以及按照排序输出至少一个目标实体中的目标实体的相关信息（203）。该方法可以提高对确定的目标实体进行排序的准确性，有助于向用户有针对性地展示各个目标实体的相关信息。

Description

用于输出信息的方法和装置
本专利申请要求于2018年8月31日提交的、申请号为201811015493.0、申请人为北京字节跳动网络技术有限公司、发明名称为“用于输出信息的方法和装置”的中国专利申请的优先权，该申请的全文以引用的方式并入本申请中。
技术领域
本申请实施例涉及计算机技术领域，具体涉及用于输出信息的方法和装置。
背景技术
知识图谱(Knowledge Graph)是一种叫做语义网络(semantic network)的知识库，即具有有向图结构的一个知识库，其中图的节点代表实体(entity)或者概念(concept)，而图的边代表实体/概念之间的各种语义关系。知识图谱可以应用于各种领域，例如信息搜索、信息推荐等领域。利用知识图谱，可以得到与表征某一信息的实体关联的其他实体，从而可以较准确地得到与该信息关联的其他信息。
发明内容
本申请实施例提出了用于输出信息的方法和装置。
第一方面，本申请实施例提供了一种用于输出信息的方法，该方法包括：从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体；对于至少一个目标实体中的目标实体，从该目标实体的属性信息中确定至少一个热度数据，其中，热度数据用于表征目标实体表征的视频的被关注程度；基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分；按照所得到的评分的大小，对至少一个目标实体进行排序，以及按照排序输出至少一个目标实体中的目 标实体的相关信息。
在一些实施例中，基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分，包括：对于所确定的至少一个热度数据中的热度数据，基于预设的、与该热度数据对应的转换方式，得到该热度数据对应的评分；基于预设的、与热度数据对应的权重值，对所确定的评分进行加权求和，得到该目标实体表征的视频的评分。
在一些实施例中，在按照所得到的评分的大小，对至少一个目标实体进行排序之前，该方法还包括：对于至少一个目标实体中的目标实体，获取预设的、该目标实体表征的视频的权限代价信息。
在一些实施例中，按照排序输出至少一个目标实体中的目标实体的相关信息，包括：按照排序，输出至少一个目标实体中的目标实体的相关信息和至少一个目标实体中的目标实体表征的视频的权限代价信息。
在一些实施例中，热度数据包括以下至少一种：目标实体表征的视频的播放量数据、目标实体表征的视频的关注量数据、目标实体表征的视频的评论量数据。
在一些实施例中，目标实体的相关信息包括以下至少一种：目标实体表征的视频的标题、目标实体表征的视频包括的图像、目标实体对应的热度数据。
第二方面，本申请实施例提供了一种用于输出信息的装置，该装置包括：确定单元，被配置成从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体；评分单元，被配置成对于至少一个目标实体中的目标实体，从该目标实体的属性信息中确定至少一个热度数据，其中，热度数据用于表征目标实体表征的视频的被关注程度；基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分；输出单元，被配置成按照所得到的评分的大小，对至少一个目标实体进行排序，以及按照排序输出至少一个目标实体中的目标实体的相关信息。
在一些实施例中，评分单元包括：转换模块，被配置成对于所确定的至少一个热度数据中的热度数据，基于预设的、与该热度数据对 应的转换方式，得到该热度数据对应的评分；计算模块，被配置成基于预设的、与热度数据对应的权重值，对所确定的评分进行加权求和，得到该目标实体表征的视频的评分。
在一些实施例中，该装置还包括：获取单元，被配置成对于至少一个目标实体中的目标实体，获取预设的、该目标实体表征的视频的权限代价信息。
在一些实施例中，输出单元进一步被配置成：按照排序，输出至少一个目标实体中的目标实体的相关信息和至少一个目标实体中的目标实体表征的视频的权限代价信息。
在一些实施例中，热度数据包括以下至少一种：目标实体表征的视频的播放量数据、目标实体表征的视频的关注量数据、目标实体表征的视频的评论量数据。
在一些实施例中，目标实体的相关信息包括以下至少一种：目标实体表征的视频的标题、目标实体表征的视频包括的图像、目标实体对应的热度数据。
第三方面，本申请实施例提供了一种服务器，该服务器包括：一个或多个处理器；存储装置，其上存储有一个或多个程序；当一个或多个程序被一个或多个处理器执行，使得一个或多个处理器实现如第一方面中任一实现方式描述的方法。
第四方面，本申请实施例提供了一种计算机可读介质，其上存储有计算机程序，该计算机程序被处理器执行时实现如第一方面中任一实现方式描述的方法。
本申请实施例提供的用于输出信息的方法和装置，通过从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体，再确定各个目标实体的热度数据，以及基于热度数据，对各个目标实体表征的视频进行评分，最后按照评分大小，对各个目标实体进行排序并按照排序输出至少一个目标实体中的目标实体的相关信息，从而可以有效地利用知识图谱中的实体的属性信息，提高对确定的目标实体进行排序的准确性，有助于向用户有针对性地展示各个目标实体的相关信息。
附图说明
通过阅读参照以下附图所作的对非限制性实施例所作的详细描述，本申请的其它特征、目的和优点将会变得更明显：
图1是本申请的一个实施例可以应用于其中的示例性系统架构图；
图2是根据本申请实施例的用于输出信息的方法的一个实施例的流程图；
图3是根据本申请实施例的用于输出信息的方法的一个应用场景的示意图；
图4是根据本申请实施例的用于输出信息的方法的又一个实施例的流程图；
图5是根据本申请实施例的用于输出信息的装置的一个实施例的结构示意图；
图6是适于用来实现本申请实施例的服务器的计算机系统的结构示意图。
具体实施方式
下面结合附图和实施例对本申请作进一步的详细说明。可以理解的是，此处所描述的具体实施例仅仅用于解释相关发明，而非对该发明的限定。另外还需要说明的是，为了便于描述，附图中仅示出了与有关发明相关的部分。
需要说明的是，在不冲突的情况下，本申请中的实施例及实施例中的特征可以相互组合。下面将参考附图并结合实施例来详细说明本申请。
图1示出了可以应用本申请实施例的用于输出信息的方法或用于输出信息的装置的示例性系统架构100。
如图1所示，系统架构100可以包括终端设备101、102、103，网络104和服务器105。网络104用以在终端设备101、102、103和服务器105之间提供通信链路的介质。网络104可以包括各种连接类型，例如有线、无线通信链路或者光纤电缆等等。
用户可以使用终端设备101、102、103通过网络104与服务器105交互，以接收或发送消息等。终端设备101、102、103上可以安装有各种通讯客户端应用，例如视频播放类应用、网页浏览器应用、搜索类应用、即时通信工具、社交平台软件等。
终端设备101、102、103可以是硬件，也可以是软件。当终端设备101、102、103为硬件时，可以是各种电子设备，包括但不限于智能手机、平板电脑、电子书阅读器、MP3播放器(Moving Picture Experts Group Audio Layer III，动态影像专家压缩标准音频层面3)、MP4(Moving Picture Experts Group Audio Layer IV，动态影像专家压缩标准音频层面4)播放器、膝上型便携计算机和台式计算机等等。当终端设备101、102、103为软件时，可以安装在上述所列举的电子设备中。其可以实现成多个软件或软件模块(例如用来提供分布式服务的软件或软件模块)，也可以实现成单个软件或软件模块。在此不做具体限定。
服务器105可以是提供各种服务的服务器，例如对终端设备101、102、103上展示的目标实体的相关信息提供支持的后台信息处理服务器。后台信息处理服务器可以对预先建立的知识图谱包括的实体进行处理，并得到处理结果(例如排序后的目标实体的相关信息)。
需要说明的是，本申请实施例所提供的用于输出信息的方法一般由服务器105执行，相应地，用于输出信息的装置一般设置于服务器105中。
需要说明的是，服务器可以是硬件，也可以是软件。当服务器为硬件时，可以实现成多个服务器组成的分布式服务器集群，也可以实现成单个服务器。当服务器为软件时，可以实现成多个软件或软件模块(例如用来提供分布式服务的软件或软件模块)，也可以实现成单个软件或软件模块。在此不做具体限定。
应该理解，图1中的终端设备、网络和服务器的数目仅仅是示意性的。根据实现需要，可以具有任意数目的终端设备、网络和服务器。
继续参考图2，示出了根据本申请的用于输出信息的方法的一个实施例的流程200。该用于输出信息的方法，包括以下步骤：
步骤201，从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体。
在本实施例中，用于输出信息的方法的执行主体(例如图1所示的服务器)可以从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体。其中，目标实体用于表征视频。上述预先建立的知识图谱可以存储在上述执行主体中，也可以存储在与上述执行主体通信连接的其他电子设备中。通常，知识图谱中的实体可以用于表征某种事物或概念(例如表征人物、地点、时间、信息等)。实体的形式可以包括以下至少一种：数字、文字、符号等。在本实施例中，知识图谱可以包括用于表征视频的实体。作为示例，预先建立的用于表征某视频的实体可以为“v-abc”，其中，“v”表示该实体用于表征视频，“abc”是用于表征该视频的标识。另外，本实施例的知识图谱还可以包括用于表征除视频以外的其他事物或概念的实体。例如预先建立的用于表征某人物的实体可以为“p-xyz”，其中，“p”表示该实体用于表征人物，“xyz”是用于表征该人物的标识。
上述表征视频的实体可以具有对应的属性信息。属性信息是与实体表征的视频相关的信息，可以包括但不限于以下至少一种：与视频相关的人物(例如视频制作者、演员、导演等)信息、与视频相关的时间(例如上映时间、拍摄时间等)信息、视频的来源信息(例如视频的播放地址、视频所在的网站名称等)、以及其他与视频内容相关的信息(例如视频简介、剧照、海报图片等)等。通常，在知识图谱中，实体和属性信息的对应关系可以用三元组形式的数据结构来表示，即“实体-属性-属性值”，其中，实体的属性信息可以包括上述属性-属性值。例如，某三元组可以为“abc123-名称-XXX”，其中，“abc123”为用于表征电影《XXX》的实体，“名称”为一种属性，“XXX”为属性值。
在本实施例中，上述执行主体可以按照各种方法从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体。作为示例，上述执行主体可以将技术人员预先输入的搜索词与各个表征视频的实体的属性信息包括的文本信息进行匹配，将包括上述搜索词的文本信 息对应的实体确定为目标实体。或者，实体可以具有标识信息，上述执行主体可以按照技术人员指定的标识信息，确定出目标实体。实践中，所确定的至少一个目标实体中的每个目标实体表征的视频可以是具有某些相同属性(例如表征的视频是同一类型、表征的视频的主演是同一人、表征的视频来自同一网站等)的实体。
步骤202，对于至少一个目标实体中的目标实体，从该目标实体的属性信息中确定至少一个热度数据；基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分。
在本实施例中，对于上述至少一个目标实体中的目标实体，上述执行主体可以执行如下步骤：
步骤2021，从该目标实体的属性信息中确定至少一个热度数据。
其中，热度数据用于表征目标实体表征的视频的被关注程度。需要说明的是，热度数据可以是数值，例如播放量、点击量等，当热度数据是数值时，数值越高，表征视频的被关注程度越高。热度数据也可以是其他非数值的数据，例如表征用户对视频进行优劣评价的信息(例如“好评”、“中评”、“差评”等)。
在本实施例的一些可选的实现方式中，热度数据可以包括但不限于以下至少一种：目标实体表征的视频的播放量数据、目标实体表征的视频的关注量数据、目标实体表征的视频的评论量数据等。热度数据可以通过各种方式获得，作为示例，播放量数据可以是上述执行主体根据目标实体的属性信息包括的网址，从该网址指示的网页中获取的目标实体表征的视频的播放量数据。另外，在这里，播放量数据可以是预设时间段(例如最近一天)内的实际播放量，也可以是预设时间段内的实际播放量与该网址所在的网站包括的视频的总播放量的比值。关注量数据可以是在上述网站上记录的、关注或收藏或点击目标实体表征的视频的用户数量。评论量数据可以是在上述网站上的、用户对目标实体表征的视频进行评论的数量。需要说明的是，目标实体的属性信息可以包括至少一个网址，相应地，对于上述各种热度数据中的每种热度数据，该种热度数据可以是上述执行主体从各个网址指示的网页中获取的热度数据的求和结果。
步骤2022，基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分。
其中，评分可以用于表征目标实体表征的视频的被关注程度，通常，评分越高，标识目标实体表征的视频被用户关注的程度越高。作为示例，当上述至少一个热度数据中的每个热度数据是数值时，上述执行主体可以将各个数值相加，将相加所得到的结果确定为该目标实体的评分值。
在本实施例的一些可选的实现方式中，上述执行主体可以按照如下步骤对该目标实体表征的视频进行评分：
首先，对于所确定的至少一个热度数据中的热度数据，基于预设的、与该热度数据对应的转换方式，得到该热度数据对应的评分。具体地，各个热度数据对应的转换方式可以相同也可以不同。一方面，当热度数据为数值时，可以将热度数据按比例换算至预设的数值范围内。例如，预设的数值范围为[0,1]，某热度数据为当天视频的播放量，则该热度数据对应的评分可以是播放量与预设的最大播放量的比值，当比值大于1时，评分确定为1分。另一方面，当热度数据为非数值数据时，可以将非数值数据转换为处于预设数值范围内的评分。例如，当热度数据为用户对视频的评价等级时，可以将评价等级按照预设的规则映射到数值范围[0,1]内(例如好评为1分，中评为0.5分，差评为0分)。
然后，基于预设的、与热度数据对应的权重值，对所确定的评分进行加权求和，得到该目标实体表征的视频的评分。具体地，每个热度数据可以对应于预设的权重值，权重值大的热度数据对所得到的目标实体表征的视频的评分的贡献程度越大。例如，至少一个热度数据包括播放量、关注量、评论量，对应的权重值分别为0.6、0.2、0.2，则目标实体表征的视频的评分为0.6×播放量+0.2×关注量+0.2×评论量。通过执行本实现方式，可以实现按照热度数据对应的权重值计算目标实体表征的视频的评分，从而可以提高根据热度数据确定评分的准确性。
步骤203，按照所得到的评分的大小，对至少一个目标实体进行 排序，以及按照排序输出至少一个目标实体中的目标实体的相关信息。
在本实施例中，上述执行主体可以按照步骤202中所得到的各个评分的大小，对至少一个目标实体进行排序，以及按照排序输出至少一个目标实体中的目标实体的相关信息。其中，相关信息可以是目标实体的属性信息包括的信息，也可以是与目标实体相关的其他信息(例如排序后的目标实体的序号)。作为示例，属性信息可以包括各种类型的子信息，子信息可以具有对应的标识或序号，以区分子信息的类别。上述执行主体可以从属性信息中提取预设类别的子信息作为相关信息。输出的排序后的目标实体的相关信息，可以更有针对性地展现目标实体，有助于用户根据相关信息的顺序查看目标实体表征的视频。
在本实施例的一些可选的实现方式中，目标实体的相关信息可以包括但不限于以下至少一种：目标实体表征的视频的标题、目标实体表征的视频包括的图像(例如视频截图、剧照、海报图片等)、目标实体对应的热度数据(例如播放量、关注量等)。
可选的，上述执行主体可以以各种方式输出目标实体的相关信息。例如，将目标实体的相关信息显示在与上述执行主体连接的显示器上，或者将目标实体的相关信息输出到与上述执行主体通信连接的终端设备(如图1所示的终端设备)上。
继续参见图3，图3是根据本实施例的用于输出信息的方法的应用场景的一个示意图。在图3的应用场景中，服务器301首先从预先建立的知识图谱302包括的、表征视频的实体中确定出三个目标实体303、304、305。其中，目标实体303、304、305是服务器301根据技术人员输入的搜索词“主演李XX电影”，在知识图谱302包括的、表征视频的实体中搜索得到的实体，即三个目标实体分别用于表征李XX主演的电影。然后，服务器301从每个目标实体的属性信息中确定出目标实体表征的视频在所属的网站的当天播放量作为热度数据，即图中的3031(对应播放量“20万”)、3041(对应播放量“18万”)、3051(对应播放量“10万”)。随后，服务器301将播放量的实际数值除以10000，得到目标实体303、304、305各自的评分3032(即“20”)、3042(即“18”)、3052(即“10”)。最后，服务器按照所得到的评分 由大到小的顺序，对目标实体303、304、305进行排序，以及将排序后的各个目标实体的相关信息输出到与服务器301连接的显示器306上显示。例如在显示器306上显示目标实体303表征的电影名称“XXX”和播放量“20万”，显示目标实体304表征的电影名称“YYY”和播放量“18万”，显示目标实体305表征的电影名称“ZZZ”和播放量“10万”。
本申请的上述实施例提供的方法，通过从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体，再确定各个目标实体的热度数据，以及基于热度数据，对各个目标实体表征的视频进行评分，最后按照评分大小，对各个目标实体进行排序并按照排序输出至少一个目标实体中的目标实体的相关信息，从而可以有效地利用知识图谱中的实体的属性信息，提高对确定的目标实体进行排序的准确性，有助于向用户有针对性地展示各个目标实体的相关信息。
进一步参考图4，其示出了用于输出信息的方法的又一个实施例的流程400。该用于输出信息的方法的流程400，包括以下步骤：
步骤401，从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体。
在本实施例中，步骤401与图2对应实施例中的步骤201基本一致，这里不再赘述。
步骤402，对于至少一个目标实体中的目标实体，从该目标实体的属性信息中确定至少一个热度数据；基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分。
在本实施例中，步骤402与图2对应实施例中的步骤202基本一致，这里不再赘述。
步骤403，对于至少一个目标实体中的目标实体，获取预设的、该目标实体表征的视频的权限代价信息。
在本实施例中，对于至少一个目标实体中的目标实体，用于输出信息的方法的执行主体(例如图1所示的服务器)可以获取预设的、该目标实体表征的视频的权限代价信息。其中，权限代价信息可以用 于表征用户欲获得目标实体表征的视频的播放权所要付出的代价。权限代价信息可以是数值，也可以是其他非数值的数据。作为示例，权限代价信息可以是目标实体表征的视频的版权价格值。或者是根据目标实体表征的视频的版权价格计算出的、表征用户付出的代价高低的信息。例如，当某目标实体表征的视频A的版权价格与视频A的单日播放量之比大于第一预设数值时，权限代价信息可以是文字信息“高”；当视频A的版权价格与视频A的单日播放量之比小于等于第一预设数值且大于等于第二预设数值时，权限代价信息可以是文字信息“中”；当视频A的版权价格与视频A的单日播放量之比小于第二预设数值时，权限代价信息可以是文字信息“低”。
步骤404，按照所得到的评分的大小，对至少一个目标实体进行排序，以及按照排序，输出至少一个目标实体中的目标实体的相关信息和至少一个目标实体中的目标实体表征的视频的权限代价信息。
在本实施例中，上述执行主体可以首先按照所得到的评分的大小，对至少一个目标实体进行排序，以及按照排序，输出至少一个目标实体中的目标实体的相关信息和至少一个目标实体中的目标实体表征的视频的权限代价信息。其中，本步骤中的对至少一个目标实体进行排序的方法与图2对应实施例中的步骤203中描述的对至少一个目标实体进行排序的方法基本相同，并且对目标实体的相关信息的描述可以参见图2对应实施例中的步骤203，这里不再赘述。
可选的，本步骤输出的目标实体的相关信息和目标实体表征的视频的权限代价信息可以输出到与上述执行主体连接的显示器上；或者将目标实体的相关信息和目标实体表征的视频的权限代价信息输出到与上述执行主体通信连接的终端设备(如图1所示的终端设备)上。从而可以向用户展示目标实体的相关信息和目标实体表征的视频的权限代价信息。有助于向用户更加有针对性地展示更多的信息。
从图4中可以看出，与图2对应的实施例相比，本实施例中的用于输出信息的方法的流程400突出了获取目标实体表征的视频的权限代价信息以及输出目标实体的权限代价信息的步骤。由此，本实施例描述的方案可以输出更多的信息，有助于向用户展示目标实体表征的 视频的权限代价信息，从而可以进一步提高向用户展示的信息的针对性。
进一步参考图5，作为对上述各图所示方法的实现，本申请提供了一种用于输出信息的装置的一个实施例，该装置实施例与图2所示的方法实施例相对应，该装置具体可以应用于各种电子设备中。
如图5所示，本实施例的用于输出信息的装置500包括：确定单元501，被配置成从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体；评分单元502，被配置成对于至少一个目标实体中的目标实体，从该目标实体的属性信息中确定至少一个热度数据，其中，热度数据用于表征目标实体表征的视频的被关注程度；基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分；输出单元503，被配置成按照所得到的评分的大小，对至少一个目标实体进行排序，以及按照排序输出至少一个目标实体中的目标实体的相关信息。
在本实施例中，确定单元501可以从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体。其中，目标实体用于表征视频。上述预先建立的知识图谱可以存储在上述装置500中，也可以存储在与上述装置500通信连接的其他电子设备中。通常，知识图谱中的实体可以用于表征某种事物或概念(例如表征人物、地点、时间、信息等)。实体的形式可以包括以下至少一种：数字、文字、符号等。在本实施例中，知识图谱可以包括用于表征视频的实体。作为示例，预先建立的用于表征某视频的实体可以为“v-abc”，其中，“v”表示该实体用于表征视频，“abc”是用于表征该视频的标识。另外，本实施例的知识图谱还可以包括用于表征除视频以外的其他事物或概念的实体。例如预先建立的用于表征某人物的实体可以为“p-xyz”，其中，“p”表示该实体用于表征人物，“xyz”是用于表征该人物的标识。
上述表征视频的实体可以具有对应的属性信息。属性信息可以是与实体表征的视频相关的信息，可以包括但不限于以下至少一种：与视频相关的人物(例如视频制作者、演员、导演等)信息、与视频相 关的时间(例如上映时间、拍摄时间等)信息、视频的来源信息(例如视频的播放地址、视频所在的网站名称等)、以及其他与视频内容相关的信息(例如视频简介、剧照、海报图片等)等。通常，在知识图谱中，实体和属性信息的对应关系可以用三元组形式的数据结构来表示，即“实体-属性-属性值”，其中，实体的属性信息可以包括上述属性-属性值。例如，某三元组可以为“abc123-名称-XXX”，其中，“abc123”为用于表征电影《XXX》的实体，“名称”为一种属性，“XXX”为属性值。
在本实施例中，上述确定单元501可以按照各种方法从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体。作为示例，上述确定单元501可以将技术人员输入的搜索词与各个表征视频的实体的属性信息包括的文本信息进行匹配，将包括上述搜索词的文本信息对应的实体确定为目标实体。或者，实体可以具有标识信息，上述确定单元501可以按照技术人员指定的标识信息，确定出目标实体。实践中，所确定的至少一个目标实体中的每个目标实体表征的视频可以是具有某些相同属性(例如表征的视频是同一类型、表征的视频的主演是同一人、表征的视频来自同一网站等)的实体。
在本实施例中，对于上述至少一个目标实体中的目标实体评分单元502可以执行如下步骤：
首先，从该目标实体的属性信息中确定至少一个热度数据。
其中，热度数据用于表征目标实体表征的视频的被关注程度。需要说明的是，热度数据可以是数值，例如播放量、点击量等。热度数据也可以是其他非数值的数据，例如表征用户对视频进行优劣评价的信息(例如“好评”、“中评”、“差评”等)。作为示例，当热度数据是数值时，数值越高，表征视频的被关注程度越高。
然后，基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分。作为示例，当上述至少一个热度数据中的每个热度数据是数值时，上述评分单元502可以将各个数值相加，将相加所得到的结果确定为该目标实体的评分值。
在本实施例中，输出单元503可以按照评分单元502所得到的各 个评分的大小，对至少一个目标实体进行排序，以及按照排序输出至少一个目标实体中的目标实体的相关信息。其中，相关信息可以是目标实体的属性信息包括的信息，也可以是与目标实体相关的其他信息(例如排序后的目标实体的序号)。作为示例，属性信息可以包括各种类型的子信息，子信息可以具有对应的标识或序号，以区分子信息的类别。上述输出单元503可以从属性信息中提取预设类别的子信息作为相关信息。输出的排序后的目标实体的相关信息，可以更有针对性地展现目标实体，有助于用户根据相关信息的顺序查看目标实体表征的视频。
在本实施例的一些可选的实现方式中，评分单元502可以包括：转换模块(图中未示出)，被配置成对于所确定的至少一个热度数据中的热度数据，基于预设的、与该热度数据对应的转换方式，得到该热度数据对应的评分；计算模块(图中未示出)，被配置成基于预设的、与热度数据对应的权重值，对所确定的评分进行加权求和，得到该目标实体表征的视频的评分。
在本实施例的一些可选的实现方式中，该装置500还可以包括：获取单元(图中未示出)，被配置成对于至少一个目标实体中的目标实体，获取预设的、该目标实体表征的视频的权限代价信息。
在本实施例的一些可选的实现方式中，输出单元503可以进一步被配置成：按照排序，输出至少一个目标实体中的目标实体的相关信息和至少一个目标实体中的目标实体表征的视频的权限代价信息。
在本实施例的一些可选的实现方式中，热度数据可以包括以下至少一种：目标实体表征的视频的播放量数据、目标实体表征的视频的关注量数据、目标实体表征的视频的评论量数据。
在本实施例的一些可选的实现方式中，目标实体的相关信息可以包括以下至少一种：目标实体表征的视频的标题、目标实体表征的视频包括的图像、目标实体对应的热度数据。
本申请的上述实施例提供的装置，通过从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体，再确定各个目标实体的热度数据，以及基于热度数据，对各个目标实体表征的视频进行 评分，最后按照评分大小，对各个目标实体进行排序并按照排序输出至少一个目标实体中的目标实体的相关信息，从而可以有效地利用知识图谱中的实体的属性信息，提高对确定的目标实体进行排序的准确性，有助于向用户有针对性地展示各个目标实体的相关信息。
下面参考图6，其示出了适于用来实现本申请实施例的服务器的计算机系统600的结构示意图。图6示出的服务器仅仅是一个示例，不应对本申请实施例的功能和使用范围带来任何限制。
如图6所示，计算机系统600包括中央处理单元(CPU)601，其可以根据存储在只读存储器(ROM)602中的程序或者从存储部分608加载到随机访问存储器(RAM)603中的程序而执行各种适当的动作和处理。在RAM 603中，还存储有系统600操作所需的各种程序和数据。CPU 601、ROM 602以及RAM 603通过总线604彼此相连。输入/输出(I/O)接口605也连接至总线604。
以下部件连接至I/O接口605：包括键盘、鼠标等的输入部分606；包括诸如阴极射线管(CRT)、液晶显示器(LCD)等以及扬声器等的输出部分607；包括硬盘等的存储部分608；以及包括诸如LAN卡、调制解调器等的网络接口卡的通信部分609。通信部分609经由诸如因特网的网络执行通信处理。驱动器610也根据需要连接至I/O接口605。可拆卸介质611，诸如磁盘、光盘、磁光盘、半导体存储器等等，根据需要安装在驱动器610上，以便于从其上读出的计算机程序根据需要被安装入存储部分608。
特别地，根据本公开的实施例，上文参考流程图描述的过程可以被实现为计算机软件程序。例如，本公开的实施例包括一种计算机程序产品，其包括承载在计算机可读介质上的计算机程序，该计算机程序包含用于执行流程图所示的方法的程序代码。在这样的实施例中，该计算机程序可以通过通信部分609从网络上被下载和安装，和/或从可拆卸介质611被安装。在该计算机程序被中央处理单元(CPU)601执行时，执行本申请的方法中限定的上述功能。
需要说明的是，本申请所述的计算机可读介质可以是计算机可读 信号介质或者计算机可读介质或者是上述两者的任意组合。计算机可读介质例如可以是——但不限于——电、磁、光、电磁、红外线、或半导体的系统、装置或器件，或者任意以上的组合。计算机可读介质的更具体的例子可以包括但不限于：具有一个或多个导线的电连接、便携式计算机磁盘、硬盘、随机访问存储器(RAM)、只读存储器(ROM)、可擦式可编程只读存储器(EPROM或闪存)、光纤、便携式紧凑磁盘只读存储器(CD-ROM)、光存储器件、磁存储器件、或者上述的任意合适的组合。在本申请中，计算机可读介质可以是任何包含或存储程序的有形介质，该程序可以被指令执行系统、装置或者器件使用或者与其结合使用。而在本申请中，计算机可读的信号介质可以包括在基带中或者作为载波一部分传播的数据信号，其中承载了计算机可读的程序代码。这种传播的数据信号可以采用多种形式，包括但不限于电磁信号、光信号或上述的任意合适的组合。计算机可读的信号介质还可以是计算机可读介质以外的任何计算机可读介质，该计算机可读介质可以发送、传播或者传输用于由指令执行系统、装置或者器件使用或者与其结合使用的程序。计算机可读介质上包含的程序代码可以用任何适当的介质传输，包括但不限于：无线、电线、光缆、RF等等，或者上述的任意合适的组合。
可以以一种或多种程序设计语言或其组合来编写用于执行本申请的操作的计算机程序代码，所述程序设计语言包括面向对象的程序设计语言—诸如Java、Smalltalk、C++，还包括常规的过程式程序设计语言—诸如“C”语言或类似的程序设计语言。程序代码可以完全地在用户计算机上执行、部分地在用户计算机上执行、作为一个独立的软件包执行、部分在用户计算机上部分在远程计算机上执行、或者完全在远程计算机或服务器上执行。在涉及远程计算机的情形中，远程计算机可以通过任意种类的网络——包括局域网(LAN)或广域网(WAN)—连接到用户计算机，或者，可以连接到外部计算机(例如利用因特网服务提供商来通过因特网连接)。
附图中的流程图和框图，图示了按照本申请各种实施例的系统、方法和计算机程序产品的可能实现的体系架构、功能和操作。在这点 上，流程图或框图中的每个方框可以代表一个模块、程序段、或代码的一部分，该模块、程序段、或代码的一部分包含一个或多个用于实现规定的逻辑功能的可执行指令。也应当注意，在有些作为替换的实现中，方框中所标注的功能也可以以不同于附图中所标注的顺序发生。例如，两个接连地表示的方框实际上可以基本并行地执行，它们有时也可以按相反的顺序执行，这依所涉及的功能而定。也要注意的是，框图和/或流程图中的每个方框、以及框图和/或流程图中的方框的组合，可以用执行规定的功能或操作的专用的基于硬件的系统来实现，或者可以用专用硬件与计算机指令的组合来实现。
描述于本申请实施例中所涉及到的单元可以通过软件的方式实现，也可以通过硬件的方式来实现。所描述的单元也可以设置在处理器中，例如，可以描述为：一种处理器包括确定单元、评分单元、输出单元。其中，这些单元的名称在某种情况下并不构成对该单元本身的限定，例如，确定单元还可以被描述为“从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体的单元”。
作为另一方面，本申请还提供了一种计算机可读介质，该计算机可读介质可以是上述实施例中描述的服务器中所包含的；也可以是单独存在，而未装配入该服务器中。上述计算机可读介质承载有一个或者多个程序，当上述一个或者多个程序被该服务器执行时，使得该服务器：从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体；对于至少一个目标实体中的目标实体，从该目标实体的属性信息中确定至少一个热度数据，其中，热度数据用于表征目标实体表征的视频的被关注程度；基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分；按照所得到的评分的大小，对至少一个目标实体进行排序，以及按照排序输出至少一个目标实体中的目标实体的相关信息。
以上描述仅为本申请的较佳实施例以及对所运用技术原理的说明。本领域技术人员应当理解，本申请中所涉及的发明范围，并不限于上述技术特征的特定组合而成的技术方案，同时也应涵盖在不脱离上述发明构思的情况下，由上述技术特征或其等同特征进行任意组合而形 成的其它技术方案。例如上述特征与本申请中公开的(但不限于)具有类似功能的技术特征进行互相替换而形成的技术方案。

Claims (14)

  1. 一种用于输出信息的方法，包括：
    从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体；
    对于所述至少一个目标实体中的目标实体，从该目标实体的属性信息中确定至少一个热度数据，其中，热度数据用于表征目标实体表征的视频的被关注程度；基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分；
    按照所得到的评分的大小，对所述至少一个目标实体进行排序，以及按照所述排序输出所述至少一个目标实体中的目标实体的相关信息。
  2. 根据权利要求1所述的方法，其中，所述基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分，包括：
    对于所确定的至少一个热度数据中的热度数据，基于预设的、与该热度数据对应的转换方式，得到该热度数据对应的评分；
    基于预设的、与热度数据对应的权重值，对所确定的评分进行加权求和，得到该目标实体表征的视频的评分。
  3. 根据权利要求1所述的方法，其中，在所述按照所得到的评分的大小，对所述至少一个目标实体进行排序之前，所述方法还包括：
    对于所述至少一个目标实体中的目标实体，获取预设的、该目标实体表征的视频的权限代价信息。
  4. 根据权利要求3所述的方法，其中，所述按照所述排序输出所述至少一个目标实体中的目标实体的相关信息，包括：
    按照所述排序，输出所述至少一个目标实体中的目标实体的相关信息和所述至少一个目标实体中的目标实体表征的视频的权限代价信息。
  5. 根据权利要求1所述的方法，其中，热度数据包括以下至少一种：目标实体表征的视频的播放量数据、目标实体表征的视频的关注量数据、目标实体表征的视频的评论量数据。
  6. 根据权利要求1-5之一所述的方法，其中，目标实体的相关信息包括以下至少一种：目标实体表征的视频的标题、目标实体表征的视频包括的图像、目标实体对应的热度数据。
  7. 一种用于输出信息的装置，包括：
    确定单元，被配置成从预先建立的知识图谱包括的、表征视频的实体中确定至少一个目标实体；
    评分单元，被配置成对于所述至少一个目标实体中的目标实体，从该目标实体的属性信息中确定至少一个热度数据，其中，热度数据用于表征目标实体表征的视频的被关注程度；基于所确定的至少一个热度数据，对该目标实体表征的视频进行评分；
    输出单元，被配置成按照所得到的评分的大小，对所述至少一个目标实体进行排序，以及按照所述排序输出所述至少一个目标实体中的目标实体的相关信息。
  8. 根据权利要求7所述的装置，其中，所述评分单元包括：
    转换模块，被配置成对于所确定的至少一个热度数据中的热度数据，基于预设的、与该热度数据对应的转换方式，得到该热度数据对应的评分；
    计算模块，被配置成基于预设的、与热度数据对应的权重值，对所确定的评分进行加权求和，得到该目标实体表征的视频的评分。
  9. 根据权利要求7所述的装置，其中，所述装置还包括：
    获取单元，被配置成对于所述至少一个目标实体中的目标实体，获取预设的、该目标实体表征的视频的权限代价信息。
  10. 根据权利要求9所述的装置，其中，所述输出单元进一步被配置成：
    按照所述排序，输出所述至少一个目标实体中的目标实体的相关信息和所述至少一个目标实体中的目标实体表征的视频的权限代价信息。
  11. 根据权利要求7所述的装置，其中，热度数据包括以下至少一种：目标实体表征的视频的播放量数据、目标实体表征的视频的关注量数据、目标实体表征的视频的评论量数据。
  12. 根据权利要求7-11之一所述的装置，其中，目标实体的相关信息包括以下至少一种：目标实体表征的视频的标题、目标实体表征的视频包括的图像、目标实体对应的热度数据。
  13. 一种服务器，包括：
    一个或多个处理器；
    存储装置，其上存储有一个或多个程序，
    当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现如权利要求1-6中任一所述的方法。
  14. 一种计算机可读介质，其上存储有计算机程序，其中，该程序被处理器执行时实现如权利要求1-6中任一所述的方法。
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