Finding top-N chance patterns with KeyGraph®-based importance

Yoshiaki Okubo, Makoto Haraguchi, Sachio Hirokawa

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

    1 Citation (Scopus)

    Abstract

    In this paper, as our first proposal, we discuss a method for finding a rare pattern, called a chance pattern, which connects a pair of more frequent patterns. Particularly, our chance pattern is defined with a KeyGraph®-based importance of patterns. More concretely speaking, a chance pattern is a pattern C which often appears in a part of documents containing a frequent pattern XL as well as in those containing another pattern XR, that is, confidence values of association rules, XL ⇒ C and X R ⇒ C, are relatively high. It would be expected that such a chance pattern C reveals a hidden and implicit relationships between X L and XR. We design clique-search-based algorithms for finding chance patterns with Top-N confidence values.

    Original languageEnglish
    Title of host publicationKnowledge-Based and Intelligent Information and Engineering Systems - 15th International Conference, KES 2011, Proceedings
    Pages457-468
    Number of pages12
    EditionPART 2
    DOIs
    Publication statusPublished - Sep 29 2011
    Event15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011 - Kaiserslautern, Germany
    Duration: Sep 12 2011Sep 14 2011

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume6882 LNAI
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011
    CountryGermany
    CityKaiserslautern
    Period9/12/119/14/11

    All Science Journal Classification (ASJC) codes

    • Theoretical Computer Science
    • Computer Science(all)

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