Wise mining method through ant colony optimization

Yang Jianxiong*, Junzo Watada

*Corresponding author for this work

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

    Abstract

    This paper proposes an algorithm for data mining named Pheromone-Miner (ant-colony-based data miner). The algorithm is inspired by both researches on the behavior of real ant colonies and data mining concepts as well as principles. The goal of Pheromone-Miner is to extract more exact knowledge from a database. Pheromone-based mining breaks through limitations of other mining approaches. We compare the performance of pheromone-miner with a general semantic miner. The accident causes discovered by ant-miner are considerably more accurate than those discovered by a general semantic miner. In a word, this evolutionary algorithm is suitable for improving the accuracy of data miners.

    Original languageEnglish
    Title of host publicationConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
    Pages1833-1839
    Number of pages7
    DOIs
    Publication statusPublished - 2009
    Event2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009 - San Antonio, TX
    Duration: 2009 Oct 112009 Oct 14

    Other

    Other2009 IEEE International Conference on Systems, Man and Cybernetics, SMC 2009
    CitySan Antonio, TX
    Period09/10/1109/10/14

    Keywords

    • Ant colony optimization algorithm
    • Data mining
    • Knowledge discovery
    • Pheromone

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Control and Systems Engineering
    • Human-Computer Interaction

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