A method for filtering social network friends based on distributed parallel processing mode

Abstract

The invention discloses a social network friend filtering method on the basis of a distributive parallel processing mode, which comprises the following steps: (1) acquiring data from a social network and storing the data according to a sequence of data acquisition; (2) filtering social behavior information in the acquired data on the basis of a distributive parallel processing framework structure so as to generate information of friends which a user follows and information of friends who follow the user; (3) filtering friend information, interest information and personal information in the acquired data on the basis of the distributive parallel processing framework structure, carrying out arrangement on the friends in sequence from small to big according to the similarity of the user and the friends, and merging the filtered information in the steps (2) and (3) by a simplifying function so as to establish mapping relations between the user and the friends who access the social behavior information of the user. The social network friend filtering method solves the problems of storage and network resource waste and reduction of user experience of the current social network and provides an accurate and high-efficiency friend filtering service.

Description

technical field [0001] The invention belongs to the technical field of distributed computing and social network, and more specifically relates to a method for filtering social network friends based on a distributed parallel processing mode. Background technique [0002] With the increasing popularity of social networks such as Twitter and Facebook, it has become a trend to make friends with similar interests through the Internet. In order to improve the user's experience in such applications, an effective way is to recommend potential friends to the user to expand their circle of friends. [0003] With the expansion of social scale and the massive growth of information, user data presents the following characteristics: diversity, heterogeneity and personalization, high concurrency and dynamics of user access, and the complexity of the data itself. With the expansion and changes of social circles, it has been difficult for users to find the information of friends they want t...

AI Technical Summary

Problems solved by technology

[0006] Aiming at the defects of the prior art, the purpose of the present invention is to provide a social network friend filtering method based on a distributed parallel processing mode, aiming to solve the waste of storage resources, waste of network resources, and degradation of user experience caused by the strategies adopted by current social networking sites problems, and provide an accurate and efficient friend filtering service

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