A microblog social circle mining method and system based on an artificial immune network

Abstract

The invention belongs to the technical field of network information processing. The invention discloses a microblog social circle mining method and system based on an artificial immune network, and the method comprises the steps: carrying out the calculation of the similarity between users through the analysis of social information and interest information between the users, measuring the relationship strength between the users through the similarity, and carrying out the comprehensive description of the relationship strength between the users; And on the basis, constructing a microblog undirected weighted network taking the users as nodes and the relationship strength as weights, and removing edges with relatively low relationship strength in the undirected weighted network to obtain a microblog user similarity network. According to the invention, an artificial immunization method with relatively high adaptability and self-adjustability is adopted; A principle and an action mechanismof a biological immune network are applied to similarity clustering of microblog users, users with high relationship strength are divided together, and one user is allowed to belong to a plurality ofsocial circles at the same time during division, so that mining of overlapped social circles is realized.

Description

technical field [0001] The invention belongs to the technical field of network information processing, and in particular relates to a microblog social circle mining method and system based on an artificial immune network. Background technique [0002] At present, the existing technologies commonly used in the industry are as follows: [0003] Weibo social network refers to the user relationship network formed when users publish, follow and interact with blog posts in Weibo. [0004] Microblog social circle mining is to use some data mining techniques to build a microblog network model, define the measurement indicators of the relationship strength between users, and accurately identify and mine the social circles to which different users belong from the huge virtual relationship network of microblog users. It is of great significance to the research on the evolution analysis of the structural characteristics of social networks, the prediction of network public opinion, and ...

AI Technical Summary

Problems solved by technology

However, these methods are limited in that they can only find a social circle in which a specified user is located, and cannot solve the problem of overlapping social circles in social networks, and the calculation efficiency is low

[0008] (2) Traditional overlapping social circle mining method

[0029] The microblog social circle mining method based on central node self-network discovery needs to define the central node first, and the effect of the social circle mining method depends on the selection of the central node. The membership index defined by the microblog social circle mining method based on user similarity is affected by The size of the social circle has too much influence, and the universality of the two algorithms is not strong

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