Abstract

Most of the existing methods for community discovery only deal with social network with a fixed structure, so they can not effectively deal with dynamic social network. This paper proposes a Multi-agent system method which is applied to real-time dynamic web texts for community discovery. This method combines the multi-agent system control mechanisms with community discovery algorithm. The approach not only divides community for the published web text, but also changes the community division according to the newly updated contents of web texts. Meanwhile, the similarity of two web texts is evaluated through similarity algorithm which compares content similarity and semantic similarity. The effectiveness of this algorithm has been tested on real web texts networks and experiment 3 illustrated the scalability of our algorithm for dynamic community discovery of web texts.

Paper Details