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中文摘要：
针对传统单纯聚类算法实现网页推荐精确度欠缺的问题,提出一种基于Web日志挖掘的个性化网页推荐模型,并实现了相应的网页推荐算法,算法结合聚类分析和关联规则挖掘,能有效实现网页推荐.实验结果表明,在保障网页页面推荐覆盖率的条件下,该方法有较高的精确度、有效性和实用性.
英文摘要：
For the traditional Web recommendation based on clustering algorithms has low recommend accuracy,a Web recommended model based on Web log mining was proposed,and a main algorithm combined with fuzzy cluster and association rule mining was presented to realize the model.Experiments show the model and the algorithm keep the Web recommending covering rate and also have a higher accuracy.
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