Information retrieval
Foundations of statistical natural language processing
Foundations of statistical natural language processing
A vector space model for automatic indexing
Communications of the ACM
Statistical mechanics of complex networks
Statistical mechanics of complex networks
Node roles and community structure in networks
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
An Algorithm to Find Overlapping Community Structure in Networks
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
HITS algorithm improvement using semantic text portion
Web Intelligence and Agent Systems
HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: users and contexts of use - Volume Part III
Hi-index | 0.00 |
Many researchers have studied complex networks such as the World Wide Web, social networks, and the protein interaction network. They have found scale-free characteristics, the small-world effect, the property of high-clustering coefficient, and so on. One hot topic in this area is community detection. For example, the community shows a set of web pages about a certain topic in the WWW. The community structure is unquestionably a key characteristic of complex networks. In this paper, we propose a new method for finding communities in complex networks. Our proposed method considers the overlaps between communities using the concept of the intersection graph. Additionally, we address the problem of edge in homogeneity by weighting edges using the degree of overlaps and the similarity of content information between sets. Finally, we conduct clustering based on modularity. And then, we evaluate our method on a real SNS network.