An Exact Algorithm for Maximum k-Plexes in Massive Graphs

Author:

Gao Jian12,Chen Jiejiang2,Yin Minghao2,Chen Rong1,Wang Yiyuan2

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. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3