Paper Info
Title
Overlapping Community Detection By Node-Weighting
Abstract
Community detection is an important task with great practical value for understanding the structure and function of complex networks. However, in many social networks, a node may belong to more than one community. Thus, the detection of overlapping community is more significant. The local expansion algorithm using seeds to find overlapping communities is becoming increasingly popular, but how to choose suitable seeds and expand the local communities effectively is still a great challenge. In this paper, we propose a new overlapping community detection algorithm based on node-weighting (OCDNW). The main idea of the algorithm is to find a good seed and then greedily expand it based on an improved community quality metric. Finally it optimizes the community structure to ensure the quality of community partitioning. Experimental results on synthetic and real world networks prove that the proposed algorithm can detect overlapping communities successfully and outperform other state-of-the-art methods.
Year
DOI
Venue
2018
10.1145/3193077.3193086
PROCEEDINGS OF THE 2018 2ND INTERNATIONAL CONFERENCE ON COMPUTE AND DATA ANALYSIS (ICCDA 2018)
Keywords
DocType
Citations 
Complex networks, Overlapping community detection, Local community expansion, Node-Weighting
Conference
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Xiangtao Chen1204.07
Juan Li200.34