Application of ART and concept similarity in E-commerce recommendation system
Ruiling Zhang · Computer Engineering and Applications Journal · 2010
E-commerce websites analyze the interests and habits of users and recommend products by recommendation system now.But the traditional recommendation systems have some shortcomings,such as data sparsity and digging out the potential demand.Therefore,by utilizing both the clustering characteristic of ART and product ontology,the design method of EC recommendation system is put forward.A concept similarity measure method based on Formal Concept Analysis(FCA) is proposed to enhance quality of recommendation when lacking for sort of user's interests.The experimental results show that this method can effectively improve the performance of the recommendation system.