Abstract
It is still undeveloped in the domain of detecting a “highly” overlapping community structure in social networks, in which networks are with high overlapping density and overlapping nodes may belong to more than two communities. In this paper, we propose an improved LFM algorithm, Parallel Hybrid Seed Expansion (PHSE), to solve this problem. In order to get nature communities, the local optimization of the fitness function and greedy seed expansion with a novel hybrid seeds selection strategy are employed. What’s more, to get a better scalability, a parallel implementation of this algorithm is provided in this paper. Significantly, PHSE has a comparable performance than LFM on both synthetic networks and real-world social networks, especially on LFR benchmark graphs with high levels of overlap.
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Wang, T., Qian, X., Xu, H. (2013). An Improved Parallel Hybrid Seed Expansion (PHSE) Method for Detecting Highly Overlapping Communities in Social Networks. In: Motoda, H., Wu, Z., Cao, L., Zaiane, O., Yao, M., Wang, W. (eds) Advanced Data Mining and Applications. ADMA 2013. Lecture Notes in Computer Science(), vol 8346. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53914-5_33
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DOI: https://doi.org/10.1007/978-3-642-53914-5_33
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