基于Web挖掘的电子商务个性化推荐系统

E-commerce personalized recommender system based on web mining

针对现有电子商务个性化推荐系统存在的不足,构建了一个基于Web挖掘的电子商务个性化推荐系统的整体架构模型,并采用了结合用户Web日志聚类和协同过滤的个性化推荐技术。可以有效地解决协同过滤技术所面临的数据稀疏和冷启动问题,提高推荐结果的准确性和有效性。

In this paper,an E-commerce recommending system model based on web mining is presented to solve the problem in the current E-commerce recommending system.The model uses the recommending technology that unifies user Web log clustering and collaborative filtering,which can solve the sparse data and cold start problems and enhance the accuracy and validity of the results recommended.