Flexi-clique: Exploring Flexible and Sub-linear Clique Structures

  • Song Kim
  • , Junghoon Kim*
  • , Susik Yoon
  • , Jungeun Kim
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Identifying cohesive subgraphs within networks is a fundamental problem in graph theory, relevant to various domains. The traditional clique problem, which finds fully connected subgraphs, often faces limitations due to its strict connectivity requirements. This paper introduces a novel degree-based relaxation model called Flexi-clique, where the degree constraint is adjusted sub-linearly based on the subgraph size. We establish that the maximum Flexi-clique problem is NP-hard and propose an efficient and effective peeling algorithm to address it. Our extensive experimental evaluation of real-world datasets demonstrates the effectiveness and efficiency of our approach in discovering large, cohesive subgraphs in networks.

Original languageEnglish
Title of host publicationCIKM 2024 - Proceedings of the 33rd ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages3832-3836
Number of pages5
ISBN (Electronic)9798400704369
DOIs
Publication statusPublished - 2024 Oct 21
Event33rd ACM International Conference on Information and Knowledge Management, CIKM 2024 - Boise, United States
Duration: 2024 Oct 212024 Oct 25

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings
ISSN (Print)2155-0751

Conference

Conference33rd ACM International Conference on Information and Knowledge Management, CIKM 2024
Country/TerritoryUnited States
CityBoise
Period24/10/2124/10/25

Bibliographical note

Publisher Copyright:
© 2024 ACM.

Keywords

  • cohesive subgraph discovery
  • graph mining

ASJC Scopus subject areas

  • General Business,Management and Accounting
  • General Decision Sciences

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