Distributed multi-relational data mining based on genetic algorithm

Wenxiang Dou, Jinglu Hu, Kotaro Hirasawa, Gengfeng Wu

研究成果: Conference contribution

3 引用 (Scopus)

抜粋

An efficient algorithm for mining important association rule from multi-relational database using distributed mining ideas. Most existing data mining approaches look for rules in a single data table. However, most databases are multi-relational. In this paper, we present a novel distributed data-mining method to mine important rules in multiple tables (relations) and combine the method with genetic algorithm to enhance the mining efficiency. Genetic algorithm is in charge of finding antecedent rules and aggregate of transaction set that produces the corresponding rule from the chief attributes. Apriori and statistic method is in charge of mining consequent rules from the rest relational attributes of other tables according to the corresponding transaction set producing the antecedent rule in a distributed way. Our method has several advantages over most exiting data mining approaches. First, it can process multi-relational database efficiently. Second, rules produced have finer pattern. Finally, we adopt a new concept of extended association rules that contain more import and underlying information.

元の言語English
ホスト出版物のタイトル2008 IEEE Congress on Evolutionary Computation, CEC 2008
ページ744-750
ページ数7
DOI
出版物ステータスPublished - 2008 11 14
イベント2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, China
継続期間: 2008 6 12008 6 6

出版物シリーズ

名前2008 IEEE Congress on Evolutionary Computation, CEC 2008

Conference

Conference2008 IEEE Congress on Evolutionary Computation, CEC 2008
China
Hong Kong
期間08/6/108/6/6

    フィンガープリント

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Theoretical Computer Science

これを引用

Dou, W., Hu, J., Hirasawa, K., & Wu, G. (2008). Distributed multi-relational data mining based on genetic algorithm. : 2008 IEEE Congress on Evolutionary Computation, CEC 2008 (pp. 744-750). [4630879] (2008 IEEE Congress on Evolutionary Computation, CEC 2008). https://doi.org/10.1109/CEC.2008.4630879