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Recognizing unexpected recurrence behaviors with fuzzy measures in sequence databases

Published: 28 October 2008 Publication History

Abstract

The recognition of unexpected behaviors in databases is an important problem in many real-world applications. In the previous studies, the unexpectedness is mainly stated within the context of the most-studied patterns, association rules, or sequential patterns. In this paper, we first propose the notion of fuzzy recurrence rule, a new kind of rule-based behavior in sequence databases, and then we introduce the problem of recognizing unexpected sequences contradicting the beliefs on fuzzy recurrence rules, with fuzzy measures. We also develop, UFR, an algorithm for discovering unexpected recurrence behaviors in a sequence database. Our approach is evaluated with Web access log data.

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  1. Recognizing unexpected recurrence behaviors with fuzzy measures in sequence databases

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    cover image ACM Other conferences
    CSTST '08: Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
    October 2008
    733 pages
    ISBN:9781605580463
    DOI:10.1145/1456223
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    Sponsors

    • The French Chapter of ACM Special Interest Group on Applied Computing
    • Ministère des Affaires Etrangères et Européennes
    • Région Ile de France
    • Communauté d'Agglomération de Cergy-Pontoise
    • Institute of Electrical and Electronics Engineers Systems, Man and Cybernetics Society
    • The European Society For Fuzzy And technology
    • Institute of Electrical and Electronics Engineers France Section
    • Laboratoire des Equipes Traitement des Images et du Signal
    • AFIHM: Ass. Francophone d'Interaction Homme-Machine
    • The International Fuzzy System Association
    • Laboratoire Innovation Développement
    • University of Cergy-Pontoise
    • The World Federation of Soft Computing
    • Agence de Développement Economique de Cergy-Pontoise
    • The European Neural Network Society
    • Comité d'Expansion Economique du Val d'Oise

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 28 October 2008

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    Author Tags

    1. fuzzy measure
    2. fuzzy recurrence rule
    3. sequence data mining
    4. unexpected recurrence behavior

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