Definition
Graph clustering refers to clustering of data in the form of graphs. Two distinct forms of clustering can be performed on graph data. Vertex clustering seeks to cluster the nodes of the graph into groups of densely connected regions based on either edge weights or edge distances. The second form of graph clustering treats the graphs as the objects to be clustered and clusters these objects on the basis of similarity. The second approach is often encountered in the context of structured or XML data.
Motivation and Background
Graph clustering is a form of graph mining that is useful in a number of practical applications including marketing, customer segmentation, congestion detection, facility location, and XML data integration (Lee et al. 2002). The graph clustering problems are typically defined into two categories:
Node clustering algorithms: Node clustering algorithms are...
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Aggarwal, C.C. (2017). Graph Clustering. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_348
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_348
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