In a social network, individuals often simultaneously belong to multiple social communities; therefore, the detection of relationships among individuals is very important. However, most of community detection methods only apply a single relationship in dynamic social networks with multi-relationships among individuals. Therefore, this study proposes a CNET Hierarchical Division Algorithm (CHDA) to detect communities efficiently. Experimental results show that the proposed CHDA could detect communities with more precise recognition, regarding their characterization. © Springer-Verlag Berlin Heidelberg 2014.
CITATION STYLE
Hsieh, T. A., Li, K. C., Huang, K. C., Hsu, K. H., Hsu, C. H., & Lai, K. C. (2014). Community identification in multiple relationship social networks. In Lecture Notes in Electrical Engineering (Vol. 274 LNEE, pp. 609–614). Springer Verlag. https://doi.org/10.1007/978-3-642-40675-1_90
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