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 :
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