DocumentCode
3067037
Title
Collaborative Filtering Recommendation Algorithm Based on Cloud Model Clustering of Multi-indicators Item Evaluation
Author
Sa, Li
Author_Institution
Liaoning Shiyou Univ., Fushun, China
fYear
2011
fDate
29-31 July 2011
Firstpage
645
Lastpage
648
Abstract
Collaborative filtering recommendation algorithm is a personalized recommendation algorithm that is used widely in e-commerce recommendation system. In this paper, a collaborative filtering recomendation algorithm based on cloud model clustering of multi-indicators item evaluation is proposed. In the algorithm, the item evaluation is the object, time weighted function is introduced to item evaluation, soft culsters item based on cloud model and gets the recommended items. The algorithm solves problems of data updating and history validity of evaluation in the collaborative filtering algorithm. Soft cluster item based on cloud model is achieved to avoid the defects bringed by hard division.
Keywords
electronic commerce; information filtering; recommender systems; cloud model clustering; collaborative filtering recommendation algorithm; e-commerce recommendation system; multiindicators item evaluation; personalized recommendation algorithm; soft cluster item; Algorithm design and analysis; Clustering algorithms; Collaboration; Filtering; Heuristic algorithms; Prediction algorithms; Real time systems; Collaborative filtering; cloud model clustering; item evaluation; multi-indicator; time_weighted;
fLanguage
English
Publisher
ieee
Conference_Titel
Business Computing and Global Informatization (BCGIN), 2011 International Conference on
Conference_Location
Shanghai
Print_ISBN
978-1-4577-0788-9
Electronic_ISBN
978-0-7695-4464-9
Type
conf
DOI
10.1109/BCGIn.2011.170
Filename
6003982
Link To Document