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基于自适应谐振理论的Web文档聚类集成方法

杨燕 靳蕃 KamelMohamed

杨燕, 靳蕃, KamelMohamed. 基于自适应谐振理论的Web文档聚类集成方法[J]. 西南交通大学学报, 2009, 22(1): 26-31.
引用本文: 杨燕, 靳蕃, KamelMohamed. 基于自适应谐振理论的Web文档聚类集成方法[J]. 西南交通大学学报, 2009, 22(1): 26-31.
YANG Yan, JIN Fan, KAMEL Mohamed. Web Document Ensemble Clustering Based on Adaptive Resonance Theory[J]. Journal of Southwest Jiaotong University, 2009, 22(1): 26-31.
Citation: YANG Yan, JIN Fan, KAMEL Mohamed. Web Document Ensemble Clustering Based on Adaptive Resonance Theory[J]. Journal of Southwest Jiaotong University, 2009, 22(1): 26-31.

基于自适应谐振理论的Web文档聚类集成方法

基金项目: 

四川省重大应用基础研究资助项目(04JY029-001-4)

详细信息
    作者简介:

    杨燕(1964- ),女,教授,博士,研究方向为数据挖掘、计算智能,电话:028-87634040,E-mail:yangyan@nec.swjtu.edu.cn

Web Document Ensemble Clustering Based on Adaptive Resonance Theory

  • 摘要: 提出了基于自适应谐振理论的Web文档聚类集成方法.该方法先用蚁群算法对Web文档进行聚类,再用ART神经网络对聚类结果集成.实验结果表明,集成后的聚类综合质量高于集成前的聚类综合质量.

     

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出版历程
  • 收稿日期:  2007-08-13
  • 刊出日期:  2009-02-18

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