Community detection in Attributed Network

By Issam Falih, Nistor Grozavu, Rushed Kanawati, Younès Bennani. 2018

48 citations recorded by the source corpus.

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. First we motivate the interest in the study of this issue. Then we review the main approaches proposed to deal with this problem. We propose a comparative study of some existing attributed network community detection algorithm on both synthetic data and on real world data.

Subfields: Artificial Intelligence, Statistical and Nonlinear Physics

Citations in the corpus

• Debiasing Community Detection: The Importance of Lowly Connected Nodes (2019, neutral): “There are some attributed community detection methods discussed in [8].”