Heterogeneous social network-based detection method

Abstract

The invention relates to the field of information science, and provides a detection method based on a heterogeneous social network, which maps the heterogeneous social network into a multidimensional matrix; determines the transition probability of the nodes and the transition probability of the relationship in the multidimensional matrix; uses random walk algorithm to obtain the balanced distribution of nodes and the balanced distribution of relationships; according to the balanced distribution of nodes and the balanced distribution of relationships, a weighted single-relationship social network is obtained; and using a single-relationship social network detection algorithm, based on the weighted single-relationship social network to obtain detection results of heterogeneous social networks. The present invention makes full use of the mutual influence of nodes and relationships in the heterogeneous social network, and fuses the heterogeneous network into a single-relationship social network with weights, and then utilizes the traditional single-relationship social network community detection method to Weighted single-relational networks for community detection.

Description

technical field [0001] The invention relates to the field of information science and provides a detection method based on a heterogeneous social network. Background technique [0002] This section aims to introduce the readers to the technologies of various aspects of the art that may be related to various aspects of the application. It is believed that this section helps to provide readers with background information so as to better understand the various aspects of the application. Accordingly, it should be understood that it should be read in this light, and not as an admission of prior art. [0003] With the rapid development of the Internet and the World Wide Web, research on Web communities and social networks based on Web communities has gradually emerged. Therefore, the method of finding the community structure in social networks has become a research hotspot in social network analysis, and there are also great research interests. Business opportunities, social netw...

AI Technical Summary

Problems solved by technology

At present, existing studies generally believe that different relationships in heterogeneous networks are independent of each other and treated equally. In fact, this is unreasonable in real life.

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