Detecting Network Communities Using Regularized Spectral Clustering Algorithm
出版社：
- 出版社：Springer
- 页数：：1-16
- 出版年：2012
摘要内容：
Abstract The progressively scale of online social network leads to the dif?culty of tradi-tional algorithms on detecting communities. We introduce an ef?cient and fast algorithm todetect community structure in social networks. Instead of using the eigenvectors in spectralclustering algorithms, we construct a target function for detecting communities. The wholesocial network communities will be partitioned by this target function. We also analyzeand estimate the generalization error of the algorithm. The performance of the algorithmis compared with the standard spectral clustering algorithm, which is applied to differentwell-known instances of social networks with a community structure, both computer gener-ated and from the real world. The experimental results demonstrate the effectiveness of thealgorithm.
关键词：
- Community detection ? Graph laplacian ? Eigenvector ?Spectral clustering algorithm ? Regularized spectral clustering algorithm
