Method for conducting friend recommendation through analysis of user active friends making will

Abstract

The invention discloses a method for conducting friend recommendation through analysis of the user active friends making will and relates to the technical field of computer social networks. The method comprises the steps that a user friends making will characteristic matrix P and a user friends making will characteristic matrix Q are initialized, a directed adjacent matrix H is worked out, inconsistency of the directed adjacent matrix H is calculated through loop iteration, the user friends making will characteristic matrix P and the user friends making will characteristic matrix Q are updated through iteration, and a new directed adjacent matrix H is worked out; according to the directed adjacent matrix H, an initiator and a receiver of each relation pair are distinguished, active friends and passive friends of the user are distinguished, and accordingly, new friends are recommended to each user. According to the method for conducting friend recommendation through analysis of the user active friends making will, the active friends making will of each user in an undirected social relation is reasonably judged, so that personal interest and friends making preference of each user can be more accurately captured, a more accurate friend recommendation service can be provided for the undirected social networks, all kinds of analysis work of the social networks can be facilitated.

Description

technical field [0001] The invention relates to the technical field of computer social networks, in particular to a method for recommending friends by analyzing users' willingness to make friends actively. Background technique [0002] Online social networks have now been integrated into people's lives. It has become a way of life for people to make friends, share information, and interact and entertain through online social networking platforms such as Renren, Weibo, and WeChat. Operators of social network platforms often hope to conduct in-depth analysis and mining of users' social relationships and social behaviors, and then provide users with personalized recommendation services to enhance user activity and stickiness. Friend recommendation is one of the most typical and common recommendation scenarios in social networks. The general method of friend recommendation is to mine and extract the user's personal preference by analyzing the user's existing friends, and then m...

AI Technical Summary

Problems solved by technology

However, in our real life, the relationship between friends is often not completely equal, and the process of relationship generation is still directional. Different users have different wishes for the generation of friend relationship, but the directionality is often impossible to observe , which makes it difficult to recommend friends in undirected social networks

If the potential direction and user willingness to make friends in the undirected relationship are not identified, it may not be possible to truly identify the user's needs and produce low-quality recommendation results

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