Method for carrying out community detection on heterogeneous social network on basis of clustering algorithm

Abstract

Provided is a method for carrying out community detection on a heterogeneous social network on the basis of a clustering algorithm. The method comprises the steps that an adjacent matrix is built; the community structure is initialized; the local modularity is calculated; a set of mark numbers of communities participating in fusion is obtained; candidate fusion sets are obtained; differences of the modularity are calculated; whether the first modularity difference and the second modularity difference meet the fusion standard or not, if yes, the mark numbers of the communities participating in fusion and the mark numbers of candidate communities are unified, and if not, the step of calculation of the local modularity is executed again; a new community structure is recorded; if community merging does not exist in the current cycle, the optimal community structure is output. According to the method for carrying out community detection on the heterogeneous social network on the basis of the clustering algorithm, due to the fact that the clustering method, the similarity vector method and the local modularity method are adopted, the methods can be effectively applied to community detection of the heterogeneous social network, and accuracy of the detection result of the heterogeneous network community structure is improved.

Description

technical field [0001] The invention belongs to the technical field of computers, and further relates to a community detection method for heterogeneous social networks based on a clustering algorithm in the technical field of social network computing. The invention can be used for community detection in complex social systems and large-scale social networks. Background technique [0002] In the existing social network community detection methods, it mainly targets the traditional network with only one kind of node. In real life, the composition of social networks is more complex than that of traditional networks, and there may be more than one type of node. A social network that contains more than one kind of nodes is called a heterogeneous social network. For example, in a movie rating tag system, three types of entities, movie, tag, and user, constitute the entire system. A user rates a movie and adds a tag, so that there is a relationship between these three entities, a...

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Problems solved by technology

The disadvantage of this method is that it can only solve the social network community detection problem composed of one kind of nodes, and does not take into account the fact that there may be multiple entities in the social system in practical applications. Therefore, this method cannot be applied to heterogeneous social networks. community detection problem

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