关键词: 数据挖掘, 规则挖掘, 电子商务, 推荐系统

Abstract: Based on the emerging relevant recommendation systems, a rule-based recommendation system prototype was implemented. Its contributions focused on coping with three essential issues to develop a recommendation system: data source, data model and recommendation strategy as a whole. To improve its flexibilities, the system employed customers purchase histories as data source, but not the commonly-used user ratings. In addition, to ensure the quantity and quality of recommendations, its underlining engine was built up on an association-sequential-rule model. A recommendation strategy based on one-round table scanning was also designed to improve the response delay. Laboratory experiment results show that this recommendation system produces a better outcome in both efficiency and quality.

Key words: data mining, rule mining, e-commerce, recommendation system