A Study of Hybrid Recommendation Algorithm Based on User
Junrui Yang, Cai Xia Yang, Xiaowei Hu · 2016
The explosive growth in the amount of available digital information and the number of visitors to the internert and the increasing of library collection have created a potential chanllenge for library service which need to recommend an item to users that he might be intersted in. How quickly and effectively suggeting avilable information to users turned into a new service direction. So Personalization recommendation technology has become a hot topic. Recently, collaborative filtering technique is the most mature and the most commonly implemented. But there are many disadvantages in parctical applications sunch as cold-start, sparsity and scalability. This paper conducted a study for sparsity issue to improve hybrid algorithm which improve confidence of recommendation technology[1].