WO2018161310A1

WO2018161310A1 - Method for classifying social network user, and client terminal

Info

Publication number: WO2018161310A1
Application number: PCT/CN2017/076142
Authority: WO
Inventors: 罗健; 熊星
Original assignee: 深圳市华第时代科技有限公司
Priority date: 2017-03-09
Filing date: 2017-03-09
Publication date: 2018-09-13

Abstract

A method for classifying a social network user, and client terminal. The method comprises: a client terminal acquiring, via a server and from a database, user information including one or more user tags (S10); and the client terminal classifying and grouping, according to the user tags, the user information (S20). The present invention enables searching and querying of user information in a weakly tied social relationship according to a user tag, thus improving a success rate of searching for valid information in a weakly tied social relationship for a user, and providing superior user experience related to a weakly tied social relationship.

Description

Social user classification method and client

Technical field

The present invention relates to the field of communications technologies, and in particular, to a social user classification method and a client.

Background technique

With the development of communication technology, there are more and more social activities established through the network. There are strong social relationships and weak social relationships in online social activities. Among them, strong social relationships refer to basically daily contact and long-term interaction. People, mutual trust in people is higher than trust in things; weak social relationships are people who are not in contact with each other, but basically friends, classmates, colleagues, relatives, or weaker micro-relationships, or People who gather in a group with the same interest or other common points on the network, weak social relationships are effective bridges for transmitting messages between different social clusters, play a very important role in the social structure, but the existing network social platform It is not yet able to provide information search and query using weak social relationships, and it is not able to provide users with a good weak social experience.

technical problem

The main purpose of the present invention is to solve the problem that the existing social network platform cannot provide information search and query using weak social relationships, and cannot provide a good weak social experience for users.

Technical solution

To achieve the above objective, the present invention provides a social user classification method, the method comprising:

The client obtains user information from the database through the server, where the user information includes one or more user tags;

The client classifies and groups the user information according to the user tag.

Preferably, the classifying and grouping the user information according to the user label according to the user label specifically includes:

Determining whether there is a plurality of user information having N identical user tags in all user information;

When there are multiple user information having N identical user tags, the plurality of user information having N identical user tags are divided into one category, and accordingly, a corresponding user classification table is generated, where N is greater than or equal to 1 Natural number

Determining whether there is a plurality of user information having M identical user tags in all user information in each category in the user classification table, where M is a natural number greater than N;

When there is a plurality of user information having M identical user tags in all user information in a category in the user classification table, the plurality of user information having M identical user tags are divided into one group, and correspondingly generated for each category User grouping table.

Preferably, after the generating the corresponding user grouping table for each category, the social user classification method further includes:

The client displays the user classification table and the user group table;

The client selects one or more user tags, and locates one or more user information from the user classification table and the user group table according to the selected user tag;

Determining, by the client, whether the located user information is included in the authenticated friend information;

When the authenticated friend information includes the located user information, the corresponding user account is obtained from the located user information, and the chat interface corresponding to the user account is displayed.

Preferably, when the authenticated friend information does not include the located user information, the social user classification method further includes:

Obtaining a corresponding user account from the located user information, and performing friend authentication according to the user account.

Preferably, the user tag is determined according to the academic information and the working background information in the user information.

In addition, to achieve the above object, the present invention further provides a client, where the client includes:

An obtaining module, configured to obtain user information from a database by using a server, where the user information includes one or more user labels;

And a classification module, configured to classify and group the user information according to the user label.

Preferably, the classification module is further configured to determine whether there is a plurality of user information having N identical user tags in all user information, and when there are multiple user information having N identical user tags, The plurality of user information of the same user label is divided into one category, and accordingly, a corresponding user classification table is generated, wherein N is a natural number greater than or equal to 1, and all user information in each category in the user classification table is determined. Whether there is a plurality of user information having M identical user tags, where M is a natural number greater than N, and when all user information in a certain category in the user classification table has multiple user information having M identical user tags, A plurality of user information having M identical user tags are divided into one group, and a corresponding user group table is generated for each category.

Preferably, the client further includes:

a communication module, configured to display the user classification table and the user group table after generating a corresponding user group table for each category, and select one or more user labels, according to the selected user label Locating one or more user information in the user classification table and the user grouping table;

a judging module, configured to determine whether the queried loyalty information includes the locating user information, and when the queried loyalty information includes the locating user information, obtain the corresponding user information from the locating user information The user account displays the chat interface corresponding to the user account.

Preferably, the determining module is further configured to: when the authenticated friend information does not include the located user information, obtain a corresponding user account from the located user information, according to the user account. Make friend authentication.

Beneficial effect

The social user classification method and the client provided by the present invention can obtain user information from a database, classify and group the user information according to user tags included in the user information, and can search for user information in a weak social relationship according to the user tag. Query to improve the success rate of users finding effective information in weak social relationships, and provide users with a good weak social experience.

DRAWINGS

FIG. 1 is a schematic flowchart diagram of an embodiment of a social user classification method according to the present invention;

2 is a schematic diagram of a specific refinement process of the user information classification and grouping according to the user label in step S20 of FIG. 1;

3 is a schematic flowchart of generating a corresponding user group table for each category in step S24 of FIG. 2;

4 is a schematic diagram of functional modules of an embodiment of a client according to the present invention;

FIG. 5 is a schematic diagram of functional modules of another embodiment of a client according to the present invention.

The implementation, functional features, and advantages of the present invention will be further described in conjunction with the embodiments.

Embodiments of the invention

The preferred embodiments described herein are to be construed as illustrative only and not limiting.

The present invention provides a social user classification method. Referring to FIG. 1, FIG. 1 is a schematic flowchart diagram of an embodiment of a social user classification method according to the present invention. In this embodiment, the social user classification method includes:

Step S10: The client obtains user information from the database through the server, where the user information includes one or more user tags, wherein the user tags are determined according to the academic information and the working background information in the user information.

The client and the server in this embodiment communicate through the network, and can fully utilize the hardware environment advantages of the client and the server, and allocate tasks to the client and the server in a reasonable manner, thereby reducing communication overhead during the running process. For example, the transmission control protocol between the client and the server (Transmission) Control Protocol, TCP), Internet Protocol (Internet Protoco, IP) and User Datagram (User Datagram) Protocol, UDP) for communication, UDP and TCP protocols are transport layer protocols, IP protocol is the network layer protocol, TCP protocol is based on the connection protocol, before the official data transmission and reception, must establish a reliable connection with the other party, the reliability Highly demanding data communication systems often use the TCP protocol to transmit data. The non-connected UDP protocol does not establish a connection with the other party and directly sends the data packet to the other party.

Step S20: The client classifies and groups the user information according to the user label.

In this embodiment, the user label is a concise and accurate summary of the user information, that is, the user label is a highly relevant keyword, and can accurately describe and classify the user information so as to be able to be customized according to requirements. User information is searched and shared. Specifically, user information having one same user label can be classified into one category, and user information having two or more identical user labels in the same category is divided into one group. Complete classification and grouping of user information.

Referring to FIG. 2, FIG. 2 is a schematic diagram of a specific refinement process in which the client classifies and groups the user information according to the user label in step S20 of FIG. The step of collecting, by the client, the user information according to the user label in the step S20 includes:

Step S21: Determine whether there is a plurality of user information having N identical user tags in all the user information, wherein the user tags are determined according to the academic information and the working background information in the user information.

Step S22: When there are multiple pieces of user information having N identical user tags, the plurality of user information having N identical user tags are divided into one category, and a corresponding user classification table is generated, where N is greater than or equal to The natural number of 1.

Step S23: Determine whether there is a plurality of user information having M identical user tags in all user information in each category in the user classification table, where M is a natural number greater than N.

Step S24: When there is a plurality of user information having M identical user tags in all user information in a category in the user classification table, the plurality of user information having M identical user tags are divided into one group, for each The category generates a corresponding user grouping table.

In the above embodiment, in the process of classifying all the user information, the user information of at least one common tag is divided into one class, and the user information in the weak social environment is classified into the maximum range, according to the user tag. A class of classified user information is grouped, which can more precisely classify user information on the basis of classification, and can improve the accuracy of positioning user information.

For example, assume that all user information includes the following four users: Zhang San, Tsinghua undergraduate, Huawei incumbent, intellectual property engineer; Li Si, Tsinghua undergraduate, Huawei incumbent, intellectual property engineer; Wang Wu, Peking University undergraduate, ZTE , intellectual property engineer; Zhao Liu, Peking University undergraduate, ZTE incumbent, software engineer. After obtaining the information of the four users mentioned above, it is determined whether there are multiple user information with N identical user tags in all user information, and N is a natural number greater than or equal to 1, when it is determined that there are Zhang San, Li Si, Wang When the information of five or three users includes the user label of “Intellectual Property Engineer”, the three users Zhang San, Li Si and Wang Wu are divided into one category, and Zhao Six is divided into one category, including Zhang San and Li. 4. A category of Wang Wu, and generating a category including Zhao Liu, generating a user classification table according to the two categories divided. Then, it is judged whether all the user information in the categories including Zhang San, Li Si, and Wang Wu have a plurality of user information having M identical user tags, wherein M is a natural number greater than N, and when it is determined that there are Zhang San and Li Si When the information of the two users includes the two user labels of "Tsinghua Undergraduate" and "Huawei in-service", the categories to which Zhang San, Li Si, and Wang Wu belong are divided into user groups including Zhang San and Li Si, and including Wang. The user grouping of five generates a user grouping table according to the divided two groups.

In the above specific example, in the process of classifying the information of four users of Zhang San, Li Si, Wang Wu and Zhao Liu, Zhang San, Li Si, Wang Wu, who have the common user label of “Intellectual Property Engineer” Divided into one category, Zhao Liu, who has the “Software Engineer” user label, is classified into another category, which can classify user information in a weak social environment to the largest extent, in the categories of Zhang San, Li Si, and Wang Wu. The user information is grouped, and Zhang San and Li Si are divided into two groups according to the two common user labels of "Tsinghua undergraduate" and "Huawei in-service", and Zhao six is divided into another group, which can be used as the basis for classification of user information. More detailed division is carried out to improve the accuracy of locating user information. When the user selects one or more user tags through the client, the related user information can be accurately located to improve communication efficiency.

Referring to FIG. 3, FIG. 3 is a schematic diagram of a flow after generating a corresponding user group table for each category in step S24 of FIG. 2. After the corresponding user grouping table is generated for each category in step S24, the social user classification method further includes:

Step S25: The client displays the user classification table and the user group table.

Step S26: The client selects one or more user tags, and locates one or more user information from the user classification table and the user grouping table according to the selected user tag.

In the above embodiment, the specific manner in which the client selects one or more user tags includes: displaying a plurality of user tags on the touch screen, and selecting one or more user tags through the touch signals received by the touch screen.

Step S27: The client determines whether the authenticated friend information includes the located user information.

In step S28, when the authenticated friend information includes the located user information, the corresponding user account is obtained from the located user information, and the chat interface corresponding to the user account is displayed.

Step S29: When the authenticated friend information does not include the located user information, the corresponding user account is obtained from the located user information, and the friend authentication is performed according to the user account.

In the above embodiment, along with the specific example used in the description of FIG. 2, it is assumed that Zhang San, Li Si, and Wang Wu, who have the "Intellectual Property Engineer" common user label, are classified into one category, and there will be "software engineer". The user's label is classified into a category. The user classification table is generated according to the two categories divided, and the user classification table is displayed. At the same time, Zhang San, who has two common user labels, “Tsinghua undergraduate” and “Huawei in-service” will be displayed. Li Si is divided into one group, and Wang Wu is divided into another group. The user group table is generated according to the divided two groups, and the user group table is displayed. When the client selects three user tags: “Intellectual Property Engineer”, “Tsinghua Undergraduate”, and “Huawei In-service”, the user information of Zhang San and Li Si is located from the user classification table and the user group table. The client judges whether the authenticated friend information includes the user information of Zhang San and Li Si. When the authenticated friend information includes the user information of the positioned Zhang San and Li Si, the positioned Zhang San and Li Si are located. In the user information, the corresponding user accounts of Zhang San and Li Si are obtained, and the chat interface corresponding to the user accounts of Zhang San and Li Si is displayed. When the authenticated friend information does not include the user information of the positioned Zhang San and Li Si, the user accounts of Zhang San and Li Si are obtained from the user information of the positioned Zhang San and Li Si, according to Zhang San, Li Si's user account is used for friend authentication.

The social user classification method provided by the foregoing embodiment can obtain user information from a database, classify and group the user information according to the user tags included in the user information, and can search and query the user information in the weak social relationship according to the user tag. Improve the success rate of users finding effective information in weak social relationships, and provide users with a good weak social experience.

The invention further provides a client. Referring to FIG. 4, FIG. 4 is a schematic diagram of functional modules of an embodiment of a client according to the present invention. In this embodiment, the client 100 includes an obtaining module 110 and a classification module 120. The obtaining module 110 is configured to obtain user information from a database by using a server, where the user information includes one or more user tags, and the user tags are determined according to the academic information and the working background information in the user information. The classification module 120 is configured to classify and group user information according to user tags.

In this embodiment, the client and the server communicate through the network, and the hardware environment advantages of the client and the server can be fully utilized, and the tasks are allocated to the client and the server in a reasonable manner, thereby reducing the communication overhead during the running process. Specifically, the client and the server communicate via TCP/IP and UDP protocols. The UDP and TCP protocols are transport layer protocols, the IP protocol is the network layer protocol, and the TCP protocol is based on the connection protocol. Before, it is necessary to establish a reliable connection with the other party. The data communication system with high reliability requirements often uses the TCP protocol to transmit data, and the non-connected UDP protocol does not establish a connection with the other party, and directly sends the data packet to the other party. It is further added that, in this embodiment, the user label is a concise and accurate summary of the user information, that is, the user label is a highly relevant keyword, and can accurately describe and classify the user information. In order to be able to retrieve and share user information according to requirements, in particular, user information with one same user tag can be divided into one category, and users with two or more identical user tags in the same category. The information is divided into groups to complete the classification and grouping of user information.

Referring to FIG. 5, FIG. 5 is a schematic diagram of functional modules of another embodiment of a client according to the present invention. In this embodiment, the client 100 includes: an obtaining module 110, a classifying module 120, a communication module 130, and a determining module 140. The obtaining module 110 is configured to obtain user information from a database by using a server, where the user information includes one or more user tags, and the user tags are determined according to the academic information and the working background information in the user information. The classification module 120 is configured to classify and group user information according to user tags.

In the above embodiment, the classification module 120 is further configured to determine whether there are multiple user information having N identical user tags in all user information, and when there are multiple user information having N identical user tags, A plurality of user information having N identical user tags is divided into one category, and accordingly, a corresponding user classification table is generated, wherein N is a natural number greater than or equal to 1, and all of the categories in the user classification table are determined. Whether there is a plurality of user information having M identical user tags, where M is a natural number greater than N, and when there is a plurality of user information having M identical user tags in all user information in a certain category in the user classification table At the same time, a plurality of user information having M identical user tags are divided into one group, and a corresponding user group table is generated for each category. In the process of classifying all user information, the user information of at least one common tag is divided into one class, and the user information in the weak social environment can be classified into the largest range, and the user tags are classified according to each category. The user information is grouped, and the user information can be divided into more detailed on the basis of classification, which can improve the accuracy of positioning the user information.

For example, assume that all user information includes the following four users: Zhang San, Tsinghua undergraduate, Huawei incumbent, intellectual property engineer; Li Si, Tsinghua undergraduate, Huawei incumbent, intellectual property engineer; Wang Wu, Peking University undergraduate, ZTE , intellectual property engineer; Zhao Liu, Peking University undergraduate, ZTE incumbent, software engineer. The classifying module 120 is specifically configured to: after obtaining the information of the four users, whether there is a plurality of user information having N identical user tags in all user information, where N is a natural number greater than or equal to 1, when determining When the information of the three users of Zhang San, Li Si and Wang Wu includes the user label of “Intellectual Property Engineer”, the three users Zhang San, Li Si and Wang Wu are divided into one category, and Zhao Six is divided into A class that generates a category including Zhang San, Li Si, and Wang Wu, and generates a category including Zhao Liu, and generates a user classification table according to the divided two categories. Then, it is judged whether all the user information in the categories including Zhang San, Li Si, and Wang Wu have a plurality of user information having M identical user tags, wherein M is a natural number greater than N, and when it is determined that there are Zhang San and Li Si When the information of the two users includes the two user labels of "Tsinghua Undergraduate" and "Huawei in-service", the categories of Zhang San, Li Si, and Wang Wu are divided into user groups including Zhang San and Li Si, and including Wang. The user grouping of five generates a user grouping table according to the divided two groups.

In the above specific example, in the process of classifying users' information of Zhang San, Li Si, Wang Wu, and Zhao Liu, Zhang San, Li Si, and Wang Wu, who have the common label of “Intellectual Property Engineers”, are divided into In the first category, Zhao Liu, who has the “Software Engineer” user label, is classified into another category, which can classify the user information in a weak social environment to the largest extent, and the categories of Zhang San, Li Si, and Wang Wu are classified according to the user label. Grouping can classify the user information more precisely based on the classification, and improve the accuracy of locating the user information. When the user selects one or more user tags through the client, the user information can be accurately located and improved. Communication efficiency.

In this embodiment, the communication module 130 is configured to display the user classification table and the user group table after generating the user classification table and the user group table, and select one or more user labels, according to the selected user label. One or more user information is located in the user classification table and the user group table. The specific manner in which the client selects one or more user tags includes: displaying a plurality of user tags on the touch screen, and selecting one of the touch signals received through the touch screen. Or multiple user tags. It should be noted that the user tag is determined according to the academic information and the working background information in the user information. The determining module 140 is configured to determine whether the authenticated friend information includes the located user information, and when the authenticated friend information includes the located user information, obtain the corresponding user account from the located user information. Display the chat interface corresponding to the user account. It is to be noted that the determining module 140 is further configured to: when the authenticated friend information does not include the located user information, obtain the corresponding user account from the located user information, and perform friend authentication according to the user account. .

In the above embodiment, it is assumed that the existing user information includes the following four pieces of user information: information of four users: Zhang San, Tsinghua undergraduate, Huawei in-service, intellectual property engineer; Li Si, Tsinghua undergraduate, Huawei in-service, intellectual property engineer Wang Wu, Peking University undergraduate, ZTE incumbent, intellectual property engineer; Zhao Liu, Peking University undergraduate, ZTE incumbent, software engineer. The classification module 120 classifies Zhang San, Li Si, and Wang Wu, which have the common user label of the “Intellectual Property Engineer”, into a category, and classifies the Zhao 6 with the “Software Engineer” user label as a category, according to the division. Two categories generate user classification tables. After the user classification table is generated, the communication module 130 is configured to display the user classification table. The classification module 120 is specifically configured to group Zhang San and Li Si, which have two common user labels of “Tsinghua undergraduate” and “Huawei in-service”, and divide Wang 5 into a group according to the division. Groups generate user grouping tables. After generating the user group table, the communication module 130 is configured to display the user group table. When the client selects three user tags of "Intellectual Property Engineer", "Tsinghua Undergraduate", and "Huawei In-service", the communication module 130 is used to user Zhang San and Li Si from the user classification table and the user group table. Information is located. The determining module 140 is configured to determine whether the authenticated friend information includes the user information of Zhang San and Li Si, and when the authenticated friend information includes the user information of the positioned Zhang San and Li Si, the positioning is performed. The user information of Zhang San and Li Si obtains the corresponding user accounts of Zhang San and Li Si, and displays the chat interface corresponding to the user accounts of Zhang San and Li Si. When the authenticated friend information does not include the user information of the positioned Zhang San and Li Si, the corresponding user accounts of Zhang San and Li Si are obtained from the user information of the positioned Zhang San and Li Si, according to Zhang. Third, Li Si's user account for friend authentication.

The client provided by the above embodiment can obtain user information from the database, classify and group the user information according to the user tags included in the user information, and can search and query the user information in the weak social relationship according to the user tag, thereby improving the user. Finding the success rate of effective information in weak social relationships provides users with a good weak social experience.

The above are only the preferred embodiments of the present invention, and are not intended to limit the scope of the invention, and the equivalent structure or equivalent process transformations made by the description of the present invention and the drawings are directly or indirectly applied to other related technical fields. The same is included in the scope of patent protection of the present invention.

Claims

A social user classification method, comprising:

The client obtains user information from the database through the server, where the user information includes one or more user tags;

The client classifies and groups the user information according to the user tag.
The social user classification method according to claim 1, wherein the classifying and grouping the user information according to the user label comprises:

Determining whether there is a plurality of user information having N identical user tags in all user information;

When there are multiple user information having N identical user tags, the plurality of user information having N identical user tags are divided into one category, and accordingly, a corresponding user classification table is generated, where N is greater than or equal to 1 Natural number

Determining whether there is a plurality of user information having M identical user tags in all user information in each category in the user classification table, where M is a natural number greater than N;

When there is a plurality of user information having M identical user tags in all user information in a category in the user classification table, the plurality of user information having M identical user tags are divided into one group, and correspondingly generated for each category User grouping table.
The social user classification method according to claim 2, wherein after the generating a corresponding user grouping table for each category, the social user classification method further comprises:

The client displays the user classification table and the user group table;

The client selects one or more user tags, and locates one or more user information from the user classification table and the user group table according to the selected user tag;

Determining, by the client, whether the located user information is included in the authenticated friend information;

When the authenticated friend information includes the located user information, the corresponding user account is obtained from the located user information, and the chat interface corresponding to the user account is displayed.
The social user classification method according to claim 3, wherein when the authenticated friend information does not include the located user information, the social user classification method further includes:

Obtaining a corresponding user account from the located user information, and performing friend authentication according to the user account.
The social user classification method according to any one of claims 1-4, wherein the user tag is determined according to the academic information and the work background information in the user information.
A client, comprising:

An obtaining module, configured to obtain user information from a database by using a server, where the user information includes one or more user labels;

And a classification module, configured to classify and group the user information according to the user label.
The client of claim 6 wherein:

The classification module is specifically configured to determine whether there are multiple user information with N identical user tags in all user information, and when there are multiple user information with N identical user tags, the N has the same user tag. The plurality of user information is divided into one category, and accordingly, a corresponding user classification table is generated, where N is a natural number greater than or equal to 1, and it is determined whether all user information in each category in the user classification table has M Multiple user information of the same user tag, where M is a natural number greater than N, and when all user information in a certain category in the user classification table has multiple user information having M identical user tags, there will be M identical The plurality of user information of the user tag is divided into one group, and a corresponding user group table is generated for each category.
The social user classification client according to claim 7, further comprising:

a communication module, configured to display the user classification table and the user group table after generating a corresponding user group table for each category, and select one or more user labels, according to the selected user label Locating one or more user information in the user classification table and the user grouping table;

a judging module, configured to determine whether the queried loyalty information includes the locating user information, and when the queried loyalty information includes the locating user information, obtain the corresponding user information from the locating user information The user account displays the chat interface corresponding to the user account.
The client of claim 8 wherein:

The determining module is further configured to: when the authenticated friend information does not include the located user information, obtain a corresponding user account from the located user information, and perform friend authentication according to the user account. .
The client according to any one of claims 6-9, wherein the user tag is determined according to academic information and work background information in the user information.