Method and system for pushing recommended friend to user of social network

• US 10,069,931 B2
• Filed: 06/25/2013
• Issued: 09/04/2018
• Est. Priority Date: 08/08/2012
• Status: Active Grant

• Current Assignee: ZTE Corporation
• Original Assignee: ZTE Corporation
• Inventors: Wei, Xing
• Primary Examiner(s): Katsikis, Kostas
• Application Number:
  US14/420,380
• Publication Number:
  US 20150215421A1
• Time in Patent Office: 1,897 Days
• Field of Search: 709204
• CPC Class Codes: G06N 5/02 Knowledge representation; Symbolic representation
• CPC Class Codes: G06Q 30/0282 Rating or review of business operators or products
• CPC Class Codes: G06Q 50/01 Social networking
• CPC Class Codes: H04L 67/306 User profiles
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34
• CPC Class Codes: H04L 67/55 Push-based network services
• CPC Class Codes: H04W 4/21 for social networking applications

Abstract

Disclosed are a method and a system for pushing recommended friends to a user on a social networking site, wherein, the method includes: automatically analyzing usage information of each user on a current social networking site to obtain feature information of each user; matching feature information of a user on the current social network with feature information of other users on the current social networking site to obtain matching goodness-of-fit values of feature information between the user and the other users; determining users corresponding to matching goodness-of-fit values which are greater than a preset goodness-of-fit value as matching users of the user; sending friend recommendation information to the user, wherein the friend recommendation information includes information of each matching user. The present document can achieve that a social networking site actively recommends friends to a user.

Claims

1. A method for pushing recommended friends to a user on a social networking site, wherein the method comprises:

automatically analyzing, by a first social networking site, usage information of each user on the first social networking site to obtain feature information of each user on the first social networking site, wherein the usage information of the each user on the first social networking site refers to information comprising personal information, habits, hobbies, and a current state shown by the each user during using the first social networking site, and the feature information of the each user on the first social networking site comprises hobbies, occupation and location of the each user on the first social networking site;

wherein automatically analyzing the usage information of the each user on the first social networking site to obtain feature information of the each user on the first social networking site comprises;

obtaining the each user'"'"'s location by analyzing the each user'"'"'s registration information;

obtaining the each user'"'"'s hobbies according to the interactions between the each user with other people on the first social networking site; and

obtaining the each user'"'"'s occupation according to information published by the each user;

receiving, by the first social networking site, usage information of each user on a second social networking site cooperating with the first social networking site, wherein the usage information of the each user on the second social networking site refers to information comprising personal information, habits, hobbies, and a current state shown by the each user during using the second social networking site;

automatically analyzing, by the first social networking site, the usage information of each user on the second social networking site cooperating with the first social networking site to obtain feature information of each user on the second social networking site, wherein the feature information of the each user on the second social networking site comprises hobbies, occupation and location of the each user on the second social networking site;

wherein automatically analyzing the usage information of the each user on the second social networking site to obtain feature information of the each user on the second social networking site comprises;

obtaining the each user'"'"'s location by analyzing the each user'"'"'s registration information;

obtaining the each user'"'"'s hobbies according to the interactions between the each user with other people on the second social networking site; and

obtaining the each user'"'"'s occupation according to information published by the each user;

matching, by the first social networking site, feature information of a user on the first social networking site with feature information of other users on the first social networking site and with feature information of other users on the second social networking site;

obtaining, by the first social networking site, based on the matching, matching goodness-of-fit values of feature information between the user and the other users;

determining, by the first social networking site, users corresponding to matching goodness-of-fit values which are greater than a preset goodness-of-fit value as matching users of the user;

sending, by the first social networking site, a friend recommendation information to the user, wherein the friend recommendation information comprises information of each matching user; and

sending, by the first social networking site, a friend recommendation information to the each matching user, wherein the friend recommendation information comprises information of the user.

2. The method of claim 1, wherein, before sending the friend recommendation information to the user, the method further comprises:

judging whether the user has already added all of the matching users as friends or not, when the user has not added all of the matching users as friends, performing an operation of sending the friend recommendation information to the user, wherein the friend recommendation information comprises information of each matching user who has not been added as a friend yet.

3. The method of claim 1, wherein, said automatically analyzing usage information of each user on the first social networking site to obtain feature information of each user comprises:

automatically analyzing usage information of each user on the first social networking site periodically according to a preset frequency to obtain feature information of each user.

4. The method of claim 1, wherein, the friend recommendation information further comprises:

a matching goodness-of-fit value of feature information between the user and each matching user, as well as matching consistent feature information.