Abstract
In order to meet users find valuable information in lots of information, the recommended system came into being. Recommended system in e-commerce platform to play the role of sales staff, recommend products to users, help users find the products, collaborative filtering technology is recommender system the application of the earliest and one of the most successful techniques, However, with the site structure of the complex, the amount of goods and users increasing, the development of collaborative filtering recommendation system faces two major challenges: to improve scalability of Collaborative filtering algorithms and reduce data sets sparse of the recommended system, Against these issues this paper proposed an improved collaborative filtering approach - Cluster-based collaborative filtering recommendation algorithms.
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