Mining closed relational graphs with connectivity constraints
作者： Xifeng Yan , X. Jasmine Zhou , Jiawei Han
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摘要: Relational graphs are widely used in modeling large scale networks such as biological and social networks. In this kind of graph, connectivity becomes critical identifying highly associated groups clusters. paper, we investigate the issues mining closed frequent with constraints massive relational where each graph has around 10K nodes 1M edges. We adopt concept edge apply results from theory, to speed up process. Two approaches developed handle different requests: CloseCut, a pattern-growth approach, splat, pattern-reduction approach. have applied these methods datasets found discovered patterns interesting.
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