Title :
Collaborative filtering recommendation algorithm based on cluster
Author_Institution :
Inf. Eng. Coll., Ningbo Dahongying Univ., Ningbo, China
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.
Keywords :
collaborative filtering; pattern clustering; recommender systems; collaborative filtering recommendation algorithm; collaborative filtering technology; e-commerce platform; pattern clustering; recommended system; sparse data sets; Atmospheric modeling; Collaboration; Databases; Filtering; Integrated circuit modeling; cluster; collaborative filtering; offline modul; online module; personalized recommendation system;
Conference_Titel :
Computer Science and Network Technology (ICCSNT), 2011 International Conference on
Conference_Location :
Harbin
Print_ISBN :
978-1-4577-1586-0
DOI :
10.1109/ICCSNT.2011.6182519