Web Association Rules Mining Using Genetic Algorithm

摘要：

Association rules are imported basis for describing Web users behavior characteristic. Traditional algorithms of Web association rules mining have relied on two user-specified thresholds: minimum support and minimum confidence. There are two significant challenges to applying these algorithms to real-world applications: exponential search space and ineffective predictive means. To circumventing these problems, we design an evolutionary mining strategy, based on a genetic algorithm,which is effective for global searching, especially when the search space is so large that it is hardly possible to use deterministic searching method. This method could be more quickly and efficiently for searching in the whole global, and extremely used for the mining association rules to large-scale database.

关键词： data mining web association rules genetic algorithm

作者: LI Zhujuan SU Yidan ZHANG Bin

作者单位: College of Computer and Electronics Information,Guangxi University Nanning, Guangxi Province, China 530004

会议类型: 国际会议

会议名称: 第二届国际计算机新科技与教育学术会议(Proceedings of the Second International Conference on Computer Science & Education ICCSE2007)

会议地点: 武汉

会议语种:英文

页码: 486-490

在线出版日期: 2007-07-25（万方平台首次上网日期，不代表论文的发表时间）