Abstract: Web usage mining is a hot research direction of Web data mining.In this paper，an improved genetic algorithm is proposed to overcome the shortage of early convergence and stagnation in the traditional genetic algorithm，which is based on unconvertible rate of crossover operator and mutation operator.Moreover，the user page interest measure threshold is introduced into the association rules mining.Lastly，the improved genetic algorithm is successfully applied to a commerce Web server log mining and the experiment results indicate that the proposed algorithm is an effective method to avoid early convergence.

Key words: Web data mining, Web usage mining, genetic algorithm, interest measure

摘要： Web使用挖掘是近年来Web数据挖掘中的研究热点。针对传统遗传算法在提取关联规则问题时常采用固定染色体交叉概率和染色体变异概率，容易出现早熟、收敛速度较慢的问题，提出了改进的遗传算法，并在关联规则的提取中增加了用户页面兴趣度这一阈值，成功地运用到某商业网站服务器日志挖掘。实验证明，这种改进的遗传算法能够有效避免早熟收敛现象，是一种有效的方法。

关键词: Web数据挖掘, Web使用挖掘, 遗传算法, 兴趣度