WO2020030959A1

WO2020030959A1 - Resource recommendation method and apparatus, device/terminal/server, and computer-readable medium

Info

Publication number: WO2020030959A1
Application number: PCT/IB2018/056489
Authority: WO
Inventors: 原英虎; 胡月鹏
Original assignee: 优视科技新加坡有限公司
Priority date: 2018-08-10
Filing date: 2018-08-27
Publication date: 2020-02-13
Also published as: CN109063157A

Abstract

Disclosed are a resource recommendation method and apparatus, a device/terminal/server, and a computer-readable medium. An embodiment of the method comprises: establishing a virtual relationship between a first user and a second user according to a pre-defined user clustering rule; and according to the virtual relationship between the first user and the second user, recommending to the second user a resource associated with the first user. According to the embodiment, the communication between users is effectively achieved, and the information connection, communication, and information sharing between a user and other users in a social network system are further achieved.

Description

The resource recommendation method and its device, device / terminal / server, and computer-readable media application requirements are submitted to the China Patent Office on August 10, 2018, with the application number 201810912187. The invention name is "Resource Recommendation Method and Device, Device, Device / Terminal / server, computer readable medium ", the priority of the Chinese patent application, the entire contents of which are incorporated herein by reference.

Technical field

The present application relates to the field of computer technology, and specifically to the field of Internet technology, and in particular, to a resource recommendation method and device, device / terminal / server, and computer-readable medium. Background technique

With the rapid development of computer technology and Internet technology, there are more and more types of social network systems in electronic devices such as mobile phones and tablet computers. People's communication methods have changed greatly, and they have gradually transitioned from face-to-face actual communication to social networking. Communicate online.

Users, such as individuals or organizations, can interact with and interact with each other through social networking systems. As the user types, the social networking system can create and store user profiles associated with the user in the social networking system. Social networking systems can send content or messages related to their services to users' mobile phones or other computing devices over one or more networks. The user may also install social applications on the user's mobile phone or other computing device, configured to access the user's user profile and other data within the social networking system.

Therefore, how to effectively solve the communication between users through the social network system has become an urgent technical problem to further realize that users can connect with, communicate with, and share information with other users in the social network system. Summary of the invention

The purpose of this application is to propose a resource recommendation method and its device, device / terminal / server, and computer-readable medium, which are configured to effectively implement communication between users and become a technical problem to be urgently solved, further realizing that users can communicate with social networks. Other users in the system connect, communicate, and share information.

In a first aspect, this application provides a resource recommendation method, which includes: Establishing a virtual relationship between a first user and a second user according to a predefined user clustering rule;

And recommending resources associated with the first user to the second user according to a virtual relationship between the first user and the second user. In a second aspect, an embodiment of the present application provides a resource recommendation device, including: a first program unit configured to establish a virtual relationship between a first user and a second user according to a predefined user clustering rule;

A second program unit is configured to recommend resources associated with the first user to the second user according to a virtual relationship between the first user and the second user.

In a third aspect, an embodiment of the present application provides a device / terminal / server, including: one or more processors;

A storage medium configured to store one or more programs,

When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of the foregoing embodiments.

In a fourth aspect, an embodiment of the present application provides a computer-readable medium on which a computer program is stored, and when the program is executed by a processor, implements a method as described in any one of the foregoing embodiments. In the resource recommendation method and device, device / terminal / server, and computer-readable medium provided in this application, a virtual relationship between a first user and a second user is established according to a predefined user clustering rule; A virtual relationship between a user and the second user, recommending the resources associated with the first user to the second user, effectively implementing communication between users, further realizing that users can communicate with social networks Other users in the system connect, communicate, and share information. BRIEF DESCRIPTION OF THE DRAWINGS

Other features, objects, and advantages of the present application will become more apparent by reading the detailed description of the non-limiting embodiments with reference to the following drawings:

FIG. I is a schematic flowchart of a resource recommendation method in Embodiment 1 of this application;

2 is a schematic flowchart of a resource recommendation method in Embodiment 2 of the present application; 3 is a schematic flowchart of a resource recommendation method in Embodiment 3 of the present application; FIG. 4 is a schematic flowchart of a resource recommendation method in Embodiment 4 of the present application;

5 is a schematic flowchart of a resource recommendation method in Embodiment 5 of the present application;

6 is a schematic flowchart of a resource recommendation method in Embodiment 6 of the present application;

7 is a schematic flowchart of a resource recommendation method in Embodiment 7 of the present application;

FIG. 8 is a schematic structural diagram of a resource recommendation device in Embodiment 8 of the present application;

FIG. 9 is a schematic structural diagram of a resource recommendation device in Embodiment 9 of this application;

FIG. 10 is a schematic structural diagram of a resource recommendation device in Embodiment 10 of the present application;

FIG. 11 is a schematic structural diagram of a resource recommendation device in Embodiment 11 of this application;

FIG. 12 is a schematic structural diagram of a resource recommendation device in Embodiment 12 of this application; FIG.

FIG. 13 is a schematic structural diagram of a resource recommendation device in Embodiment 13 of this application;

FIG. 14 is a schematic structural diagram of a resource recommendation device in Embodiment 14 of this application;

FIG. 15 is a schematic structural diagram of a device / terminal / server in Embodiment 15 of this application.

FIG. 16 is a hardware structure of a device / terminal / server in Embodiment 16 of the present application. detailed description

The following describes the present application in detail with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only configured to explain the related invention, but not to limit the invention. It should also be noted that, for convenience of description, only the parts related to the related invention are shown in the drawings.

It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The application will be described in detail below with reference to the drawings and embodiments.

In the following embodiments of the present application, a virtual relationship between a first user and a second user is established according to a predefined user clustering rule; and according to the virtual relationship between the first user and the second user, Recommending the resources associated with the first user to the second user.

In the following embodiments, a specific application to a short video application is used as an example for description, for example, short video content recommendation is performed between users of the short video application. Therefore, the resources in the following embodiments specifically refer to short videos in a short video application scenario. The first user generally refers to a user who recommends a short video, and the second user generally refers to a user who accepts the recommendation. Therefore, the first user and the second user may have a one-to-many relationship or a many-to-one relationship.

However, it should be noted that the following embodiments only take the short video scene as an example. For description, for a person of ordinary skill in the art, inspired by the following embodiments, it can be applied to other application scenarios with social attributes without creative work.

FIG. I is a schematic flowchart of a resource recommendation method in Embodiment 1 of the present application. As shown in FIG. I, it may include the following steps S101-S102:

S101. According to a predefined user clustering rule, establish an index table between the unique user identifiers corresponding to the first user and the second user respectively to establish a virtual relationship.

In this embodiment, the user clustering rule is mainly configured to classify users based on a certain aspect of similarity between users. A vector for classifying users is defined in the user clustering rule, and the vector may have one or more dimensions, that is, the similarity between users is determined from the perspective of these dimensions. That is, the clustering rule includes a user classification vector, and the user classification vector has one or more classification dimensions, and the similarity between users is determined according to the user classification vector.

In this embodiment, the user may refer to a temporary user who is legally registered or dynamically logged on the short video application platform. For legally registered users, a unique user ID is assigned by the short video application platform, and for temporary users who log in dynamically, the temporary user name that is logged in, such as an instant messaging account or mobile phone number, is recorded on the short video application platform. And because the instant messaging account or mobile phone number is also unique and can identify different users, the instant messaging account or mobile phone number can be directly used as the user identification.

For this reason, in step S101 or before step S101, the short video application platform may first obtain the user identifications of the first user and the second user from the background or front-end device. If the user identifications are obtained from the front-end device, the user The identification can be stored directly on the front-end device.

For example, after the user identification is obtained, the data of the above-mentioned classification dimension is collected based on the user identification to form a user classification vector for the user, and then the similarity between users is determined according to the similarity between the user classification vectors. . For example, if the cosine similarity between two user classification vectors is greater than a set similarity threshold, the two users can be classified into the same category. The similarity threshold can be obtained based on big data analysis.

Therefore, when it is determined that there are similarities between two or more users, the user identities of these users can be directly associated to form an index table, and the virtual relationship between users is recorded through the index table. However, it should be noted that, because a user may have similarities with multiple users, the index table reflects that the relationship between users may be a mesh structure. S102. Recommend resources associated with the first user to the second user according to a virtual relationship between the first user and the second user.

In this embodiment, since it is determined through the previous steps that the first user and the second user belong to the same type of users and have a certain similarity, the short video that the first user watches or loves can be recommended to the second user. During specific recommendation, the recommended short video may be directly added to the short video list of the second user, or the URL address of the recommended short video may be added to the short video list of the second user, or through a private message. Sending or notifying the second user in a manner; or sending or notifying the second user in a comment manner, thereby effectively implementing communication between different users, further realizing that the user can perform information connection with other users in the social network system, Communicate and share information.

In order to make it easy for the second user to know which are the recommended short videos, in this embodiment, the recommended short videos are highlighted for display, for example, they have prominent effects such as permanent presence. FIG. 2 is a schematic flowchart of a resource recommendation method in Embodiment 2 of the application. As shown in FIG. 2, in this embodiment, the following steps S201-S203 may be included:

S201. Determine attribute vectors of the first user and the second user.

In this embodiment, the attribute vector is a multi-dimensional attribute vector, where each dimension attribute represents a value of an attribute of a user, and describes the characteristics and social attributes of the user. Social attributes are, for example, interests, educational background, and professional background. User characteristics are, for example, the user ’s gender, age, and birth place.

In this embodiment, relevant data reflecting user characteristics and social attributes required to determine a user ’s attribute vector may be obtained directly from the short video application platform. For this reason, when a user registers, a dialog box for collecting these data is configured.

5202. Establish a virtual relationship according to a predefined user clustering rule and attribute vectors corresponding to the first user and the second user, respectively.

In this embodiment, an attribute vector similarity calculation rule is configured in the user clustering rule. After determining the user's attribute vector, the vector value of the attribute vector or radar chart of different users is calculated according to the similarity calculation rule set therein. Then, it is determined whether there is similarity between users according to the similarity of vector values or the similarity of radar charts. For example, the vector value corresponding to the first user and the vector value corresponding to the second user are within the same set range, then the first user and the second user are similar and can be classified as the same user. For another example, if the first user The radar images corresponding to the second user have a high degree of coincidence, so the first user and the second user have similarities and can be classified as the same user.

S203. Recommend resources associated with the first user to the second user according to the virtual relationship between the first user and the second user.

In this embodiment, step S203 is similar to the above step S102, that is, when a specific recommendation is made, the recommended short video may be directly added to the short video list of the second user, or the URL of the recommended short video is added to the first In the short video list of the two users, the second user is sent or notified through a private message; or the second user is sent or notified through a comment. In order to make it easier for the second user to know which are the recommended short videos, in this embodiment, the recommended short videos are highlighted for display, for example, they have prominent effects such as permanent presence.

In this embodiment, resources associated with the first user may be directly pushed to the second user according to a virtual relationship between the first user and the second user; or, if the first user The two users enable the resource subscription mode, and then push the resources associated with the first user to the second user. FIG. 3 is a schematic flowchart of a resource recommendation method in Embodiment 3 of the present application. As shown in FIG. 3, in this embodiment, the following steps S301-S303 may be included:

S301. Determine behavior records of the first user and the second user.

In this embodiment, a user behavior database is configured on a device / terminal / server of the short video application platform, and is configured to record behavior data of users using the short video platform. The user behavior refers to a related operation of the user in the application website, for example, Browse a user's information, preview a short video, download a short video, watch a short video, rate a short video, write a comment for a short video, etc.

In addition, it should be noted that application websites in different fields can make recommendations based on more comprehensive and richer user information by sharing user behavior information, so that the quality of recommendations can be jointly improved, such as between application websites in different fields. You can cooperate to share user information through the application website alliance.

The user behavior database has social data sources (such as social networking sites). User behavior records include: user identification, user account, application domain, application name, time when the behavior occurred, and project name (including short video name, short video profile, etc. ), Short video tags (including short video categories, short-sighted producers, short video uploaders, short video keywords, etc.), related links (packages Including the link to the short video introduction page), user actions (including browsing, viewing, downloading, commenting, purchasing, etc.), and user feedback (including short video ratings, reviews, film reviews, etc.).

5302. Establish a virtual relationship according to a predefined user clustering rule and behavior records corresponding to the first user and the second user respectively.

In this embodiment, a user clustering rule is configured with a behavior record vector, and a user is configured with a behavior record vector. The behavior record vector has multiple dimensions, and each dimension corresponds to a category of user behavior. After the user behavior is determined in step S301, the corresponding user behavior is directly mapped to the behavior record vector. The user clustering rule is configured with an attribute vector similarity calculation rule. After the user's attribute vector is determined, the similarity is set according to it The calculation rule calculates vector values of behavior record vectors of different users, and then determines whether there is similarity between users according to the similarity of the vector values. For example, the vector value corresponding to the first user and the vector value corresponding to the second user are in the same set range, then the first user and the second user are similar and can be classified as the same user.

5303. Recommend resources associated with the first user to the second user according to a virtual relationship between the first user and the second user.

In this embodiment, step S303 is similar to the above step S102, that is, when a specific recommendation is made, the recommended short video may be directly added to the short video list of the second user, or the URL address of the recommended short video is added to the first In the short video list of the two users, the second user is sent or notified through a private message; or the second user is sent or notified through a comment. In order to make it easier for the second user to know which are the recommended short videos, in this embodiment, the recommended short videos are highlighted for display, for example, they have prominent effects such as permanent presence. FIG. 4 is a schematic flowchart of a resource recommendation method in Embodiment 4 of the present application. As shown in FIG. 4, in this embodiment, the following steps S401-S403 may be included:

S401. Determine interest tags of the first user and the second user.

In this embodiment, a user label may be formed based on the user behavior collected in the third embodiment, and a user may be configured with multiple different user labels.

In specific implementation, the user tags may be directly stored in the above-mentioned user behavior database.

5402. Establish a virtual relationship according to a predefined user clustering rule and the interest tags corresponding to the first user and the second user, respectively.

In this embodiment, the user clustering rule is determined by comparing the similarity of user tags. The similarity between the first user and the second user is used to establish a virtual relationship.

If the user tags can be classified into several categories, the similarity between the users can be determined by comparing the vectors in the manner of setting vectors described above.

S403. Based on the virtual relationship between the first user and the second user, recommend resources associated with the first user to the second user.

In this embodiment, step S303 is similar to the above step S102, that is, when a specific recommendation is made, the recommended short video may be directly added to the short video list of the second user, or the URL address of the recommended short video is added to the first In the short video list of the two users, the second user is sent or notified through a private message; or the second user is sent or notified through a comment. In order to make it easier for the second user to know which are the recommended short videos, in this embodiment, the recommended short videos are highlighted for display, for example, they have prominent effects such as permanent presence. FIG. 5 is a schematic flowchart of a resource recommendation method in Embodiment 5 of the present application. As shown in FIG. 5, in this embodiment, the following steps S501-S503 may be included:

S501. According to a predefined user clustering rule, a user relationship topology is established by using the first user and the second user as nodes, and the user relationship topology characterizes the virtual relationship.

In this embodiment, a user topology may be formed based on the user behavior and user attributes in the foregoing embodiments. The user is the central node of the topology, and the user behavior and user attributes are the peripheral nodes of the topology. The similarity of the topological structure establishes the user relationship topological structure. The predefined user clustering rules are similarity rules based on topology.

S502. Recommend resources associated with the first user to the second user according to a virtual relationship between the first user and the second user.

In this embodiment, step S303 is similar to the above step S102, that is, when a specific recommendation is made, the recommended short video may be directly added to the short video list of the second user, or the URL address of the recommended short video is added to the first In the short video list of the two users, the second user is sent or notified through a private message; or the second user is sent or notified through a comment. In order to make it easy for the second user to know which are the recommended short videos, in this embodiment, the recommended short videos are set with an emphasis on the display, for example, they have prominent effects such as permanent presence. FIG. 6 is a schematic flowchart of a resource recommendation method in Embodiment 6 of the present application. As shown in FIG. 6, in this embodiment, the following steps S601-S603 may be included:

5601. Generate electronic business cards of the first user and the second user.

In this embodiment, an electronic business card of a user may be formed based on the user behavior, user attributes, and the like in the foregoing embodiment, and the user identification is directly used as the ID of the electronic business card, and the electronic business card has user behavior and user attributes.

5602. Establish a virtual relationship between the first user and the second user according to a predefined user clustering rule and electronic business cards corresponding to the first user and the second user, respectively.

In this embodiment, the predefined user clustering rule is a similarity rule based on an electronic business card.

5603. Recommend resources associated with the first user to the second user according to a virtual relationship between the first user and the second user.

In this embodiment, a recommendation list may also be generated in step S603, where the recommendation list includes multiple resources associated with the first user, and different resources have different recommendation priorities; The resources are recommended to the second user in batches or one by one.

Specifically, for example, according to the set recommendation priority threshold, resources that are greater than the recommendation priority threshold are selected from the recommendation list in batches or recommended to the second user one by one. FIG. 7 is a schematic flowchart of a resource recommendation method in Embodiment 7 of the present application. As shown in FIG. 7, in this embodiment, the following steps S701-S703 may be included:

5701. Establish a virtual relationship between the first user and the second user according to a predefined user clustering rule.

5702. Recommend resources associated with the first user to the second user according to a virtual relationship between the first user and the second user.

In this embodiment, steps S701 and S702 may refer to the description in the foregoing embodiment.

5703. Acquire a consumption result of the resource recommended by the second user, to update the user clustering rule according to the consumption result.

For example, if the second user previews the recommended resource, the information that the recommended resource has been consumed is generated and pushed to the first user, and the recommended information that the resource has been consumed is used as the information. Consumption results.

In this embodiment, the feedback of the consumption result makes the entire recommendation process a closed For example, if the short video recommended by the first user is consumed by the second user, it indicates that the second user is indeed interested in the short video recommended by the first user, and a recommendation of this type of short video may be added later. In order to increase the recommendation of the video, the classification tag of the short video may be recorded in the user clustering rule, so that the similarity of the user may be directly determined according to the classification tag.

FIG. 8 is a schematic structural diagram of a resource recommendation device in Embodiment 8 of the present application; as shown in FIG. 8, it may include:

The first program unit 801 may be configured to establish a virtual relationship between a first user and a second user according to a predefined user clustering rule;

The second program unit 802 may be configured to recommend resources associated with the first user to the second user according to a virtual relationship between the first user and the second user.

In some embodiments, the first user and the second user have unique user identifiers. Correspondingly, the first program unit may be further configured to establish the first user and the second user according to a predefined user clustering rule. Index tables between unique user IDs corresponding to users to establish virtual relationships.

For a detailed description of FIG. 8, refer to FIG. 1 described above. FIG. 9 is a schematic structural diagram of a resource recommendation device according to Embodiment 9 of the present application. As shown in FIG. 9, in addition to the foregoing first program unit 801 and second program unit 802, it may further include a third program unit 803, which may Configured to determine attribute vectors of the first user and the second user;

The first program unit may be further configured to establish a virtual relationship according to a predefined user clustering rule IJ, and attribute vectors corresponding to the first user and the second user, respectively.

For a detailed description of FIG. 9, refer to FIG. 2 described above. FIG. 10 is a schematic structural diagram of a resource recommendation device according to Embodiment 10 of the present application. As shown in FIG. 10, in addition to the foregoing first program unit 801 and second program unit 802, it may further include: a fourth program unit 804, which may Configured to determine behavior records of the first user and the second user;

Further, the first program unit may be further configured to establish a virtual relationship according to a predefined user clustering rule and behavior records corresponding to the first user and the second user respectively. For a detailed description of FIG. 10, refer to FIG. 3 described above. FIG. 11 is a schematic structural diagram of a resource recommendation device according to Embodiment 11 of the present application. As shown in FIG. 11, in addition to the above-mentioned first program unit 801 and second program unit 802, it further includes: a fifth program unit 805. Configured to determine interest tags of the first user and the second user;

Further, the first program unit may be further configured to establish a virtual relationship according to a predefined user clustering rule and interest tags corresponding to the first user and the second user, respectively.

For a detailed description of FIG. 11, refer to FIG. 4 described above.

In other embodiments, the first program unit may be further configured to establish a user relationship topology structure using the first user and the second user as nodes according to a predefined user clustering rule, and the user relationship topology structure is characterized The virtual relationship. For a detailed description of the topology, see Figure 5 above. FIG. 12 is a schematic structural diagram of a resource recommendation device according to Embodiment 12 of the present application. As shown in FIG. 12, in addition to the first program unit 801 and the second program unit 802 described above, it may further include a sixth program unit 806, May be configured to generate electronic business cards of the first user and the second user;

Further, the first program unit may be further configured to establish, according to a predefined user clustering rule and an electronic business card corresponding to the first user and the second user, respectively, Virtual relationship.

Further, the second program unit may be further configured to directly push the resources associated with the first user to the second user according to a virtual relationship between the first user and the second user; Alternatively, if the resource subscription mode is enabled for the second user, the resources associated with the first user are pushed to the second user.

For a detailed description of FIG. 11, refer to FIG. 6 described above. FIG. 13 is a schematic structural diagram of a resource recommendation device according to Embodiment 13 of the present application. As shown in FIG. 13, in addition to the foregoing first program unit 801 and second program unit 802, it may further include: a seventh program unit 807, May be configured to generate a recommendation list, where the recommendation list Including a plurality of resources associated with the first user, and different resources have different recommendation priorities;

In this embodiment, the second program unit may be further configured to, according to a virtual relationship between the first user and the second user, recommend a plurality of resources in the recommendation list in batches or one by one to Mentioned second user.

In this embodiment, the seventh program unit may be further configured to filter resources greater than the recommended priority threshold from the recommended list to recommend to the second user according to the set recommended priority threshold. FIG. 14 is a schematic structural diagram of a resource recommendation device according to Embodiment 14 of the present application. As shown in FIG. 14, in addition to the first program unit 801 and the second program unit 802 described above, it may further include an eighth program unit 808, It may be configured to obtain a consumption result of the recommended resource by the second user, to update the user clustering rule according to the consumption result.

In this embodiment, if the second user previews the recommended resource, the eighth program unit may be further configured to generate information that the recommended resource has been consumed and push it to the first user, The recommended information that the resource has been consumed is used as the consumption result. FIG. 15 is a schematic structural diagram of a device / terminal / server in Embodiment 15 of the present application. The device / terminal / server may include:

One or more processors 1501;

The storage medium 1502 may be configured to store one or more programs,

When the one or more programs are executed by the one or more processors, the one or more processors implement the resource recommendation method as described in any one of the foregoing embodiments. 16 is a hardware structure of a device / terminal / server in Embodiment 16 of the present application; as shown in FIG. 16, the hardware structure of the server may include: a processor 1601, a communication interface 1602, a storage medium 1603, and a communication bus 1604;

The processor 1601, the communication interface 1602, and the storage medium 1603 complete communication with each other through the communication bus 1604;

Optionally, the communication interface 1602 may be an interface of a communication module, such as an interface of a GSM module. The processor 1601 may be specifically configured to: according to a predefined user clustering rule, Establishing a virtual relationship between a first user and a second user; and recommending resources associated with the first user to the second user according to the virtual relationship between the first user and the second user.

The processor 1601 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc .; it may also be a digital signal processor (DSP), an application specific integrated circuit (ASIC) ), Ready-made programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. Various methods, steps, and logical block diagrams disclosed in the embodiments of the present application may be implemented or executed. A general-purpose processor may be a microprocessor, or the processor may be any conventional processor or the like.

The storage medium 1603 may be, but is not limited to, a random access storage medium (Random Access Memory, RAM), a read-only storage medium (Read Only Memory, ROM), and a programmable read-only storage medium (Programmable Read-Only Memory, PROM) , Erasable Programmable Read-Only Memory (EPROM), Electric Erasable Programmable Read-Only Memory (EEPR0M), etc. In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart may be implemented as a computer software program. For example, embodiments of the present disclosure include a computer program product including a computer program borne on a computer-readable medium, the computer program containing program code configured to perform the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through a communication section, and / or installed from a removable medium. When the computer program is executed by a central processing unit (CPU), the above functions defined in the method of the present application are performed. It should be noted that the computer-readable medium described in this application may be a computer-readable signal medium or a computer-readable storage medium or any combination of the foregoing. The computer-readable medium may be, for example, but is 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 storage media may include, but are not limited to: electrical connections with one or more wires, portable computer disks, hard disks, random access storage media (RAM), read-only storage media (ROM), erasable Type programmable read-only storage media (EPR0M or flash memory), optical fiber, portable compact disk read-only storage media (CD-ROM), optical storage media pieces, magnetic storage media pieces, Or any suitable combination of the above. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program, and the program may be used by or in combination with an instruction execution system, apparatus, or device. In this application, 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 may also be any computer-readable medium other than a computer-readable storage medium, and the computer-readable medium may send, propagate, or transmit a program configured to be used by or in combination 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, wire, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

The computer program code configured to perform the operations of the present application may be written in one or more programming languages or a combination thereof, the programming languages including an object-oriented programming language 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. In the case of a remote computer, the remote computer can be connected to a user's computer through any kind of network: including a local area network (LAN) or wide area network (WAN), or it can be connected to an external computer (such as through an Internet service provider via the Internet Connection).

The flowchart and block diagrams in the accompanying drawings illustrate the architecture, functions, and operations of possible implementations of systems, methods, and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a portion of a code, which module, program segment, or portion of the code contains one or more logic functions configured to implement a specified logic function. Executable instructions. There are specific sequence relationships in the above specific embodiments, but these sequence relationships are only exemplary. In specific implementation, these steps may be fewer, more or the execution order may be adjusted. That is, in some alternative implementations, the functions marked in the boxes may 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. It should also be noted that each block in the block diagrams and / or flowcharts, And the combination of the blocks in the block diagrams and / or flowcharts may be implemented by a dedicated hardware-based system that performs specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

The units described in the embodiments of the present application may be implemented in a software manner, or may be implemented in a hardware manner. The described unit may also be provided in a processor, for example, it may be described as: A processor includes a virtual relationship establishment unit and a resource recommendation unit. The names of these units do not constitute a limitation on the unit itself in some cases. For example, the virtual relationship establishing unit may also be described as "establishing a first user and a second user according to a predefined user clustering rule. The unit of virtual relationship. "

As another aspect, the present application also provides a computer-readable medium having stored thereon a computer program, which is executed by a processor to implement a method as described in any one of the foregoing embodiments.

As another aspect, the present application also provides a computer-readable medium, which may be included in the device described in the foregoing embodiments; or may exist alone without being assembled into the device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the device, the device is caused to: establish a relationship between the first user and the second user according to a predefined user clustering rule. Virtual relationship; recommending resources associated with the first user to the second user according to the virtual relationship between the first user and the second user.

The expressions “first,“ second, ”“ the first, ”or“ the second ”used in various embodiments of the present disclosure may modify various components regardless of order and / or importance, but These expressions do not limit the corresponding components. The above expressions are only configured for the purpose of distinguishing elements from other elements. For example, the first user equipment and the second user equipment represent different user equipments, although both are user equipments. For example, in Without departing from the scope of the present disclosure, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element.

When an element (eg, a first element) is referred to as being "(operably or communicably) coupled" or "(operably or communicably) coupled to" another element (eg, a second element) When an element (for example, a second element) or "connected to" another element (for example, a second element) is understood to mean that the one element is directly connected to the other element or the one element is via another element (for example, The third element) is indirectly connected to the other element. Rather, it is understood that when an element (eg, a first element) is referred to as being "directly connected" or "directly coupled" to another element (second element) In this case, no component (for example, a third component) is inserted between the two.

The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solution of the specific combination of the above technical features, but also covers the above technical features or Other technical solutions formed by arbitrarily combining their equivalent features. For example, a technical solution formed by replacing the above features with technical features disclosed in the present application (but not limited to) with similar functions.

Claims

Claim

A resource recommendation method, comprising:

Establishing a virtual relationship between a first user and a second user according to a predefined user clustering rule;

And recommending resources associated with the first user to the second user according to a virtual relationship between the first user and the second user.

2. The method according to claim 1, wherein the first user and the second user have unique user identifiers respectively; and correspondingly, the first user and the second user are established according to a predefined user clustering rule. 3. The virtual relationship between users includes: establishing an index table between the unique user identifiers respectively corresponding to the first user and the second user according to a predefined user clustering rule to establish a virtual relationship.

3. The method according to claim 1, further comprising: determining an attribute vector of the first user and the second user;

Correspondingly, establishing a virtual relationship between a first user and a second user according to a predefined user clustering rule includes: according to a predefined user clustering rule, attributes corresponding to the first user and the second user respectively Vectors establish virtual relationships.

The method according to claim 1, further comprising: determining behavior records of the first user and the second user;

Correspondingly, establishing a virtual relationship between the first user and the second user according to a predefined user clustering rule includes: according to the predefined user clustering rule, the behaviors corresponding to the first user and the second user respectively Records establish virtual relationships.

The method according to claim 1, further comprising: determining an interest label of the first user and the second user;

Correspondingly, establishing a virtual relationship between the first user and the second user according to a predefined user clustering rule includes: according to the predefined user clustering rule, the interests corresponding to the first user and the second user respectively Tags establish virtual relationships.

The method according to claim 1, characterized in that, establishing a virtual relationship between a first user and a second user according to a predefined user clustering rule comprises: according to a predefined user clustering rule, The first user and the second user establish a user relationship topology structure for a node, and the user relationship topology structure characterizes the virtual relationship.

The method according to claim 1, further comprising: generating electronic business cards of the first user and the second user;

Correspondingly, establishing a virtual relationship between a first user and a second user according to a predefined user clustering rule includes: according to a predefined user clustering rule and the first user and the second user respectively correspond An electronic business card to establish a virtual relationship between the first user and the second user.

The method according to claim 1, wherein, according to a virtual relationship between the first user and the second user, a resource associated with the first user is recommended to the second user Including: pushing resources associated with the first user directly to the second user according to the virtual relationship between the first user and the second user; or, if the second user enables In the resource subscription mode, the resources associated with the first user are pushed to the second user.

The method according to claim 1, further comprising: generating a recommendation list, wherein the recommendation list includes a plurality of resources associated with the first user, and different resources have different recommendation priorities;

Correspondingly, recommending resources associated with the first user to the second user according to the virtual relationship between the first user and the second user includes: according to the first user and the second user The virtual relationship between the second users recommends the multiple resources in the recommendation list to the second user in batches or one by one.

10. The method according to claim 9, further comprising: according to a set recommendation priority threshold, to filter out from the recommendation list a resource greater than the recommendation priority threshold to recommend to the second user. .

11. The method according to claim 1, further comprising: obtaining a consumption result of the resource recommended by the second user, to update the user clustering rule according to the consumption result.

12. The method according to claim 11, further comprising: if the second user previews the recommended resource, generating information that the recommended resource has been consumed and pushing it to the first A user recommends the information that the resource has been consumed as the consumption result.

13. The method according to any one of claims 1-12, further comprising: performing highlighted display processing on the recommended resources according to a set display rule.

14. A resource recommendation device, comprising:

A first program unit configured to establish a virtual relationship between a first user and a second user according to a predefined user clustering rule;

15. The device according to claim 14, wherein the first user and the second user are assigned unique user identifications; correspondingly, the first program unit is further configured to gather users according to a predefined user. The class rule establishes an index table between the unique user identifiers respectively corresponding to the first user and the second user to establish a virtual relationship.

16. The apparatus according to claim 14, further comprising: a third program unit configured to determine attribute vectors of the first user and the second user;

The first program unit is further configured to establish a virtual relationship according to a predefined user clustering rule and attribute vectors corresponding to the first user and the second user, respectively.

17. The apparatus according to claim 14, further comprising: a fourth program unit configured to determine behavior records of the first user and the second user;

The first program unit is further configured to establish a virtual relationship according to a predefined user clustering rule and behavior records corresponding to the first user and the second user respectively.

18. The apparatus according to claim 14, further comprising: a fifth program unit configured to determine interest tags of the first user and the second user;

The first program unit is further configured to establish a virtual relationship according to a predefined user clustering rule and the interest tags respectively corresponding to the first user and the second user.

19. The apparatus according to claim 14, wherein the first program unit is further configured to establish a user relationship topology using the first user and the second user as nodes according to a predefined user clustering rule. The user relationship topology characterizes the virtual relationship.

20. The device according to claim 14, further comprising: a sixth program unit configured to generate electronic business cards of the first user and the second user;

The first program unit is further configured to establish a virtual relationship between the first user and the second user according to a predefined user clustering rule and an electronic business card corresponding to the first user and the second user, respectively.

21. The apparatus according to claim 14, wherein the second program sheet Yuan is further configured to directly push the resources associated with the first user to the second user according to the virtual relationship between the first user and the second user; or, if the second user is enabled If a resource subscription mode is used, the resources associated with the first user are pushed to the second user.

22. The apparatus according to claim 14, further comprising: a seventh program unit configured to generate a recommendation list, wherein the recommendation list includes multiple resources associated with the first user, and different resources Have different recommendation priorities;

The second program unit is further configured to recommend a plurality of resources in the recommendation list to the second user in batches or one by one according to the virtual relationship between the first user and the second user.

23. The apparatus according to claim 22, wherein the seventh program unit is further configured to filter resource recommendations greater than the recommendation priority threshold from the recommendation list according to a set recommendation priority threshold. To the second user.

24. The apparatus according to claim 14, further comprising: an eighth program unit configured to obtain a result of consumption of the recommended resource by the second user to update the resource according to the consumption result User clustering rules.

25. The device according to claim 24, wherein if the second user previews the recommended resource, the eighth program unit is further configured to generate information that the recommended resource has been consumed And pushing to the first user, the recommended information that the resource has been consumed is used as the consumption result.

26. — devices / terminals / servers, including:

One or more processors;

A storage medium configured to store one or more programs,

When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1-13.

27. A computer-readable medium having stored thereon a computer program, characterized in that when the program is executed by a processor, the method according to any one of claims 1-13 is implemented.