Mining useful time graph patterns on extensively discussed topics on the web
DASFAA'10 Proceedings of the 15th international conference on Database systems for advanced applications
On fast enumeration of pseudo bicliques
IWOCA'10 Proceedings of the 21st international conference on Combinatorial algorithms
Dense subgraph maintenance under streaming edge weight updates for real-time story identification
Proceedings of the VLDB Endowment
User community reconstruction using sampled microblogging data
Proceedings of the 21st international conference companion on World Wide Web
Denser than the densest subgraph: extracting optimal quasi-cliques with quality guarantees
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
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The problem of finding dense structures in a given graph is quite basic in informatics including data mining and data engineering. Clique is a popular model to represent dense structures, and widely used because of its simplicity and ease in handling. Pseudo cliques are natural extension of cliques which are subgraphs obtained by removing small number of edges from cliques. We here define a pseudo clique by a subgraph such that the ratio of the number of its edges compared to that of the clique with the same number of vertices is no less than a given threshold value. In this paper, we address the problem of enumerating all pseudo cliques for a given graph and a threshold value. We first show that it seems to be difficult to obtain polynomial time algorithms using straightforward divide and conquer approaches. Then, we propose a polynomial time, polynomial delay in precise, algorithm based on reverse search. The time complexity for each pseudo clique is O(Δlog |V|+min {Δ 2,|V|+|E|}). Computational experiments show the efficiency of our algorithm for both randomly generated graphs and practical graphs.