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Lecture Notes in Computer Science
Attributed multi-graphs are data structures to model realworld networks of objects which have rich properties/attributes and they are connected by multiple types of edges. Clustering attributed multigraphs has several real-world applications, such as recommendation systems and targeted advertisement. In this paper, we propose an efficient method for Clustering Attributed Multi-graphs with Information Ranking, namely CAMIR. We introduce an iterative algorithm that ranks the different vertexdoi:10.1007/978-3-319-22849-5_29 fatcat:idq3pbksezdxbhaudl74pltrca