Method and device for mining social circle based on microblog interaction relationship

Abstract

The invention discloses a social circle digging method and device based on microblog interactive relationships. The method includes the steps of A, acquiring a collection of microblog users interacted with a target microblog user; B, building a user relationship topology map according to the interactive relationships, digging to obtain totally-linked sub-maps, calculating utility value of each totally-linked sub-map and saving; C, aiming at each totally-linked sub-map, generating an expansion microblog user collection according to the interactive relationships; D, acquiring the microblog users which are interacted with an optional microblog user in the microblog user collection and do not belong to the microblog user collection, adding the microblog users to the saved totally-linked sub-maps; E, calculating the utility values of the added microblog users after and before being added to the collection, adding the microblog users to the new collection if the utility values increase; F, judging whether microblog user selection is completed or not, if not, traversing the expansion microblog user collection, returning to the step D, or else, forming the social circle collection. By the method, the social circle and interest circle of a user can be dug.

Description

technical field [0001] The present invention relates to social network (SNS, Social NetWorking Services) and data mining technology, in particular to a method and device for mining social circles based on microblog interaction relationships. Background technique [0002] As a part of SNS application, microblog (microblogging) is an information sharing, dissemination and acquisition platform based on the relationship between microblog users. Microblog users can use personal PCs, mobile phones and other terminal devices to share information through microblog messages or microblog pictures. To express one's emotions and share with microblog users who follow oneself, so as to realize instant sharing of personal information and interaction between microblog users, which is the fastest growing Internet business at present. [0003] On Weibo and SNS, Weibo users expect to obtain information about social circles that have common interests or business needs with themselves, so as to ...

AI Technical Summary

Problems solved by technology

However, the maximum clique structure algorithm requires the acquisition of the full China Unicom subgraph, that is, any two nodes in the obtained full China Unicom subgraph have edge connections, which has very strong constraints, so that the obtained full China Unicom subgraph contains a relatively small number of Weibo users. It is difficult for Weibo users to obtain the required business information from the recommended social circles, which makes the efficiency of the recommended All-China Unicom sub-graph (social circles) low, which cannot meet the business needs of Weibo users and reduces the number of Weibo users. business experience

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