Searching cliques in a fuzzy graph based on an evolutionary and biological method

Ikno Kim, Junzo Watada

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

    Abstract

    In this paper, a new and systematic approach for the integration of fuzzy-based methods and biological computation, named as an evolutionary and biological method, is proposed for searching cliques in a fuzzy graph. When dealing with a number of nodes in a graph, the most intractable problem is often detecting the maximum clique, which is automatically obtained from finding a solution to the arranged cliques in descending order. The evolutionary and biological method is proposed to identify all the cliques and to arrange them in a fuzzy graph, and then to structure all the nodes in the graph, based on the searched cliques, in different hierarchical levels. This challenging approach, involving the integration of two techniques, provides a new and better method for solving clique problems.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages166-173
    Number of pages8
    Volume5712 LNAI
    EditionPART 2
    DOIs
    Publication statusPublished - 2009
    Event13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009 - Santiago
    Duration: 2009 Sep 282009 Sep 30

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume5712 LNAI
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2009
    CitySantiago
    Period09/9/2809/9/30

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

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