Friend relation mining method based on user behaviors in social network

Abstract

The invention discloses a friend relation mining method based on user behaviors in a social network. The friend relation mining method comprises the following steps: (1) respectively establishing a bipartite graph and a directed transition network, namely user-restaurant and user-taste based on record data of existing social behaviors of users; (2) respectively extracting characteristic variables for characterizing social behaviors between two users about a node or a connection side according to a network topology relation; (3) carrying out 10-fold cross-validation on all sample data by using a machine learning classifier model xgboost, training and establishing a user relation predictor model; and (4) taking the average value of 10-fold verification results as a final evaluation result of the model. The friend relation mining method is capable of mapping social behaviors of people to the network, reflecting common variables of the social behaviors by using network topology characteristics and enabling the result of the predicted friend relation between the users to be high in accuracy, and is favorable for guiding the users to find appropriate new friends and helpful for businesses to recommend more valuable information.

Description

technical field [0001] The invention relates to the fields of data mining and recommendation systems, in particular to a method for mining friend relationships in a social network based on user behavior. Background technique [0002] Domestic social networks emerged around 2005, imitating the applications of American social platforms such as Friendster and Facebook, and a number of social networking sites such as Xiaonei (later Renren), 51.com, Douban, Ruolin, and Tianji. The service has been launched successively. Especially in 2008, Kaixin.com launched social network games such as "buying and selling friends", "grabbing parking spaces", and "stealing vegetables", which made Kaixin.com quickly become popular among white-collar workers, catching up with Renren.com, the "boss" of the social platform at that time. . After more than ten years of development of social platforms, WeChat and Weibo, the mainstream domestic platforms, integrate social networking, shopping, and fin...

AI Technical Summary

Problems solved by technology

[0005] In order to overcome the disadvantage that the traditional friendship prediction model cannot maintain a high level of both accuracy and recall, the present invention proposes a social network based on user behavior that takes both accuracy and recall into account and has a good prediction effect Method of Mining Chinese Friendship Relationship

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