Multilevel k-way partitioning scheme for irregular graphs
Journal of Parallel and Distributed Computing
Diffusion Kernels on Graphs and Other Discrete Input Spaces
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Automatic multimedia cross-modal correlation discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 15th international conference on World Wide Web
Local Graph Partitioning using PageRank Vectors
FOCS '06 Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
Growth of the flickr social network
Proceedings of the first workshop on Online social networks
WAW'07 Proceedings of the 5th international conference on Algorithms and models for the web-graph
Overlapping Community Detection by Collective Friendship Group Inference
ASONAM '10 Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining
Advantage of overlapping clusters for minimizing conductance
LATIN'12 Proceedings of the 10th Latin American international conference on Theoretical Informatics
Clustered embedding of massive social networks
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Vertex neighborhoods, low conductance cuts, and good seeds for local community methods
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
DEMON: a local-first discovery method for overlapping communities
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
On the separability of structural classes of communities
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
Overlapping community detection at scale: a nonnegative matrix factorization approach
Proceedings of the sixth ACM international conference on Web search and data mining
Scalable and Memory-Efficient Clustering of Large-Scale Social Networks
ICDM '12 Proceedings of the 2012 IEEE 12th International Conference on Data Mining
Overlapping community detection in networks: The state-of-the-art and comparative study
ACM Computing Surveys (CSUR)
The Journal of Machine Learning Research
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Community detection is an important task in network analysis. A community (also referred to as a cluster) is a set of cohesive vertices that have more connections inside the set than outside. In many social and information networks, these communities naturally overlap. For instance, in a social network, each vertex in a graph corresponds to an individual who usually participates in multiple communities. One of the most successful techniques for finding overlapping communities is based on local optimization and expansion of a community metric around a seed set of vertices. In this paper, we propose an efficient overlapping community detection algorithm using a seed set expansion approach. In particular, we develop new seeding strategies for a personalized PageRank scheme that optimizes the conductance community score. The key idea of our algorithm is to find good seeds, and then expand these seed sets using the personalized PageRank clustering procedure. Experimental results show that this seed set expansion approach outperforms other state-of-the-art overlapping community detection methods. We also show that our new seeding strategies are better than previous strategies, and are thus effective in finding good overlapping clusters in a graph.