Abstract
In complex network analysis, the local community detection problem is getting more and more attention. Because of the difficulty to get complete information of the network, such as the World Wide Web, the local community detection has been proposed by researcher. That is, we can detect a community from a certain source vertex with limited knowledge of an entire graph. The previous methods of local community detection now are more or less inadequate in some places. In this paper, We propose a method called W, which assumes that a “good” community is covered with a “bridge” to other communities, and through these “bridges” the community should have little overlap with the community to be found. The results of experiments show that whether in computer-generated random graph or in the real networks, our method can effectively solve the problem of the local community detection.
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Zhang, X., Xia, Z., Wang, J. (2016). Local Community Detection Based on Bridges Ideas. In: Tan, Y., Shi, Y. (eds) Data Mining and Big Data. DMBD 2016. Lecture Notes in Computer Science(), vol 9714. Springer, Cham. https://doi.org/10.1007/978-3-319-40973-3_41
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DOI: https://doi.org/10.1007/978-3-319-40973-3_41
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