The maximum k-plex, a generalization of maximum clique, is used to cope with a great number of real-world problems. The aim of this paper is to propose a novel exact k-plex algorithm that can deal with large-scaled graphs with millions of vertices and edges. Specifically, we first propose several new graph reduction methods through a careful analyzing of structures of induced subgraphs. Afterwards, we present a preprocessing method to simplify initial graphs. Additionally, we present a branch-and-bound algorithm integrating the reduction methods as well as a new dynamic vertex selection mechanism. We perform intensive experiments to evaluate our algorithm, and show that the proposed strategies are effective and our algorithm outperforms state-of-the-art algorithms, especially for real-world massive graphs.
CITATION STYLE
Gao, J., Chen, J., Yin, M., Chen, R., & Wang, Y. (2018). An exact algorithm for maximum k-plexes in massive graphs. In IJCAI International Joint Conference on Artificial Intelligence (Vol. 2018-July, pp. 1449–1455). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2018/201
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