Method and system for friend recommendation based on similar associations in social network

Abstract

The invention discloses a method for friend recommendation based on similar associations in a social network and belongs to the field of data mining and information retrieval. Social associations in the social network are found through social information of users, a rule for calculating association similarity is raised from the two aspects of the structure and the attribute, the users are classified through the topological structure of user nodes in the associations, the roles of the nodes in the network are defined by analyzing the roles and the status of the user nodes in the belonging associations and other associations, and the users of the same type or various types corresponding to the similar associations are recommended to the users of various types in the target association to serve as friend recommendation sets. By the adoption of the method, traditional similarity calculation between single users is expanded into similarity calculation between the associations, and the traditional friend recommendation operation between the users is expanded into the operation that the users are classified through role discovery and the users of the same type or various types are recommended to the users of various types in the target association. The method can be widely applied to the related fields of the social network, electronic commerce and the like.

Description

technical field [0001] The invention belongs to the field of data mining and information retrieval, and relates to a social network recommendation technology and a link prediction technology, in particular to a friend recommendation method based on similar communities in a social network. Background technique [0002] With the advent of the information society, the Internet has become an indispensable part of people's daily life. Online social networking has become one of the hottest products on the Internet in recent years. However, due to the information overload of social networking sites, it is difficult to continue to use traditional information retrieval methods. In order to reduce the waste of time and resources and improve the efficiency of users to obtain information, it is necessary to study more effective rapid positioning and mining to meet the individual needs of users. The method of information resources and recommendation technology are proposed and developed...

AI Technical Summary

Problems solved by technology

[0006] To sum up, most of the traditional friend recommendations are only carried out between single users. When calculating the similarity, only the topological structure of the users in the network and their own characteristic information are considered. Few researchers combine the relevant theories of the community and ignore the Users mostly exist in social networks in the form of groups, and the behavior of individual users is usually influenced by the community they belong to. The behavior and preferences of users belonging to similar communities may also be similar, and it is easier to become friends

Images