DocumentCode
2898197
Title
A Neural Networks-Based Clustering Collaborative Filtering Algorithm in E-Commerce Recommendation System
Author
Mai, Jianying ; Fan, Yongjian ; Shen, Yanguang
Author_Institution
Artillery Command Acad. PLA, China
fYear
2009
fDate
7-8 Nov. 2009
Firstpage
616
Lastpage
619
Abstract
E-commerce recommendation system is one of the most important and the most successful application field of data mining technology. Recommendation algorithm is the core of the recommendation system. In this paper, a neural networks-based clustering collaborative filtering algorithm in e-commerce recommendation system is designed, trying to establish an classifier model based on BP neural network for the pre-classification to items and giving realization of clustering collaborative filtering algorithm and BP neural network algorithm, and carrying on the analysis and discussion to this algorithm from multiple aspects. This algorithm is helpful to improve sparsity problem of collaborative filtering algorithm and to form the more effective and the more accurate recommendation result.
Keywords
backpropagation; data mining; electronic commerce; groupware; information filtering; neural nets; pattern classification; pattern clustering; recommender systems; backpropagation neural network; classifier model; clustering collaborative filtering algorithm; data mining technology; e-commerce recommendation system; Algorithm design and analysis; Clustering algorithms; Data mining; Filtering algorithms; Information systems; International collaboration; Nearest neighbor searches; Neural networks; Programmable logic arrays; Real time systems; clustering algorithm; collaborative filtering algorithm; neural networks; recommendation algorithm; recommendation system;
fLanguage
English
Publisher
ieee
Conference_Titel
Web Information Systems and Mining, 2009. WISM 2009. International Conference on
Conference_Location
Shanghai
Print_ISBN
978-0-7695-3817-4
Type
conf
DOI
10.1109/WISM.2009.129
Filename
5368343
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