Affiliation:
1. College of Information Science and Technology, Dalian Maritime University, China
2. School of Computer Science and Information Technology, Northeast Normal University, China
Abstract
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.
Publisher
International Joint Conferences on Artificial Intelligence Organization
Cited by
13 articles.
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1. A local search algorithm with movement gap and adaptive configuration checking for the maximum weighted s-plex problem;Engineering Applications of Artificial Intelligence;2024-07
2. On Searching Maximum Directed $(k, \ell)$-Plex;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13
3. Quantum Algorithms for the Maximum K-Plex Problem;2024 IEEE 40th International Conference on Data Engineering (ICDE);2024-05-13
4. Maximum k-Plex Computation: Theory and Practice;Proceedings of the ACM on Management of Data;2024-03-12
5. Efficient Exact Minimum k-Core Search in Real-World Graphs;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21