Structure and attributes community detection: comparative analysis of composite, ensemble and selection methods

In recent years due to the rise of social, biological, and other rich content graphs, several new graph clustering methods using structure and node's attributes have been introduced. In this paper, we compare our novel clustering method, termed Selection method, against seven clustering methods: three structure and attribute methods, one structure only method, one attribute only method, and two ensemble methods. The Selection method uses the graph structure ambiguity to switch between structure and attribute clustering methods. We shows that the Selection method out performed the state-of-art structure and attribute methods.