关键词: Web使用挖掘, 页面关联规则, 访问模式聚类, 个性化推荐, Web挖掘

Abstract: Combining the association rules discovered from pageviews with clustering analysis of access patterns, two methods are presented for personalized recommendation. The first is to take the clustering analysis as a pre-processing procedure for association rules discovery, and the second is to have the association rules supplement clustering analysis. A comparison of the measure of recommendation is made between the two methods and using separately the association rules from pageviews or the clustering analysis of access patterns. The result of comparative testing shows that the first method can improve greatly the precision rate of recommendation, whereas the second one has comparatively high coverage rate of recommendation. Combining the association rules with clustering analysis is unable to improve both the measure precision and coverage rate of recommendation simultaneously.