37,273 research outputs found
Overlapping Community Detection using Local Seed Expansion
Communities are usually groups of vertices which have higher probability of being connected to each other than to members of other groups. Community detection in complex networks is one of the most popular topics in social network analysis. While in real networks, a person can be overlapped in multiple communities such as family, friends and colleagues, so overlapping community detection attracts more and more attention. Detecting communities from the local structural information of a small number of seed nodes is the successful methods for overlapping community detection. In this work, we propose an overlapping community detection algorithm using local seed expansion approach. Our local seed expansion algorithm selects the nodes with the highest degree as seed nodes and then locally expand these seeds with their entire vertex neighborhood into overlapping communities using Personalized PageRank algorithm. We use F1_score( node level detection ) and NMI( community level detection ) measures to assess the performances of the proposed algorithm by comparing the proposed algorithm’s detected communities with ground_truth communities on many real_world networks. Experimental results show that our algorithm outperforms over other overlapping community detection methods in terms of accuracy and quality of overlapped communities
Seeding for pervasively overlapping communities
In some social and biological networks, the majority of nodes belong to
multiple communities. It has recently been shown that a number of the
algorithms that are designed to detect overlapping communities do not perform
well in such highly overlapping settings. Here, we consider one class of these
algorithms, those which optimize a local fitness measure, typically by using a
greedy heuristic to expand a seed into a community. We perform synthetic
benchmarks which indicate that an appropriate seeding strategy becomes
increasingly important as the extent of community overlap increases. We find
that distinct cliques provide the best seeds. We find further support for this
seeding strategy with benchmarks on a Facebook network and the yeast
interactome.Comment: 8 Page
- …