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CORR
2012
Springer

Mining Attribute-structure Correlated Patterns in Large Attributed Graphs

8 years 5 months ago
Mining Attribute-structure Correlated Patterns in Large Attributed Graphs
In this work, we study the correlation between attribute sets and the occurrence of dense subgraphs in large attributed graphs, a task we call structural correlation pattern mining. A structural correlation pattern is a dense subgraph induced by a particular attribute set. Existing methods are not able to extract relevant knowledge regarding how vertex attributes interact with dense subgraphs. Structural correlation pattern mining combines aspects of frequent itemset and quasi-clique mining problems. We propose statistical significance measures that compare the structural correlation of attribute sets against their expected values using null models. Moreover, we evaluate the interestingness of structural correlation patterns in terms of size and density. An efficient algorithm that combines search and pruning strategies in the identification of the most relevant structural correlation patterns is presented. We apply our method for the analysis of three real-world attributed graphs: ...
Arlei Silva, Wagner Meira Jr., Mohammed J. Zaki
Added 20 Apr 2012
Updated 20 Apr 2012
Type Journal
Year 2012
Where CORR
Authors Arlei Silva, Wagner Meira Jr., Mohammed J. Zaki
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