Many real-world phenomena such as social networks and biological networks can be modeled as graphs. Discovering dense sub-graphs from these graphs may be able to find interesting facts about the phenomena. Quasi-cliques are a type of dense graphs, which is close to the complete graphs. In this paper, we want to find all maximal quasi-cliques containing a target vertex in the graph for some applications. A quasi-clique is defined as a maximal quasi-clique if it is not contained by any other quasi-cliques. We propose an algorithm to solve this problem and use several pruning techniques to improve the performance. Moreover, we propose another algorithm to solve a special case of this problem, i.e. finding the maximal cliques. The experiment results reveal that our method outperforms the previous work both in real and synthetic datasets in most cases.
DATA 2015 - 4th International Conference on Data Management Technologies and Applications, Proceedings, (), 5-15 4th International Conference on Data Management Technologies and Applications, DATA 2015; Colmar, Alsace; France; 20 July 2015 到 22 July 2015; 代碼 113501