Detecting Topic-oriented Overlapping Community Using Hybrid Hypergraph Model
Keywords:
information network, overlapping community detection, topic-oriented, hybrid hypergraph modelAbstract
A large number of emerging information networks brings new challenges to the overlapping community detection. The meaningful community should be topicoriented. However, the topology-based methods only reflect the strength of connection, but ignore the consistency of the topics. This paper explores a topic-oriented overlapping community detection method for information work. The method utilizes a hybrid hypergraph model to combine the node content and structure information naturally. Two connections for hyperedge pair, including real connection and virtual connection are defined. A novel hyperedge pair similarity measure is proposed by combining linearly extended common neighbors metric for real connection and incremental fitness for virtual connection. Extensive experiments on two real-world datasets validate our proposed method outperforms other baseline algorithms.References
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