On Triangulation-based Dense Neighborhood Graphs Discovery

This paper introduces a new definition of dense subgraph pattern, the DN-graph. DN-graph considers both the size of the sub-structure and the minimum level of interactions between any pair of the vertices. The mining of DN-graphs inherits the difficulty of finding clique, the fully-connected subgraphs. We thus opt for approximately locating the DN-graphs using the state-ofthe-art graph triangulation methods. Our solution consists of a family of algorithms, each of which targets a different problem setting. These algorithms are iterative, and utilize repeated scans through the triangles in the graph to approximately locate the DN-graphs. Each scan on the graph triangles improves the results. Since the triangles are not physically materialized, the algorithms have small memory footprint. With our solution, the users can adopt a “pay as you go” approach. They have the flexibility to terminate the mining process once they are satisfied with the quality of the results. As a result...

• Type: Journal
• Year: 2010
• Where: PVLDB
• Authors: Nan Wang, Jingbo Zhang, Kian-Lee Tan, Anthony K. H. Tung
• Keywords: Algorithms, Dense Subgraph Pattern, PVLDB 2010, Triangles