Abstract
Graph clustering techniques are very useful for detecting densely connected groups in large graphs. Many existing graph clustering methods mainly focus on the topological structure, but ignore the vertex properties. Existing graph clustering methods have been recently extended to deal with nodes attribute. In this paper we propose a new method which uses the nodes attributes information along with the topological structure of the network in the clustering process. Experimental results demonstrate the effectiveness of the proposed method through comparisons with the state-of-the-art graph clustering methods.
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Falih, I., Grozavu, N., Kanawati, R., Bennani, Y. (2018). ANCA : Attributed Network Clustering Algorithm. In: Cherifi, C., Cherifi, H., Karsai, M., Musolesi, M. (eds) Complex Networks & Their Applications VI. COMPLEX NETWORKS 2017. Studies in Computational Intelligence, vol 689. Springer, Cham. https://doi.org/10.1007/978-3-319-72150-7_20
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DOI: https://doi.org/10.1007/978-3-319-72150-7_20
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