Measuring and Extracting Proximity in Networks (2006)
Proceedings of the 12th ACM Int. Conference on Knowledge Discovery and Data Mining (KDD'06)
Measuring distance or some other form of proximity between objects is a standard data mining tool. Connection subgraphs were recently proposed as a way to demonstrate proximity between nodes in networks. We propose a new way of measuring and extracting proximity in networks called “cycle free effective conductance” (CFEC). Our proximity measure can handle more than two endpoints, directed edges, is statistically well-behaved, and produces an effectiveness score for the computed subgraphs. We provide an efficient algorithm. Also, we report experimental results and show examples for three large network data sets: a telecommunications calling graph, the IMDB actors graph, and an academic co-authorship network. [via]
http://www.research.att.com/~yehuda/pubs/p245...
proximity
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