DocumentCode :
1962681
Title :
Pre-filling Based on Community for Sparsity in Collaborative Filtering
Author :
Yu, Li ; Meng, Zhaoli ; Wang, Rong
Author_Institution :
Sch. of Inf., Renmin Univ. of China, Beijing
fYear :
2008
fDate :
23-25 May 2008
Firstpage :
41
Lastpage :
45
Abstract :
Collaborative filtering is a key technique in recommender system and applied widely in E-commerce. In reality, due to data sparseness, similarity of users is computed wrongly, which results that really similar users maybe filtered out while false similar users are exploited to produce recommendation. In this paper, two pre-filling methods based on community, respectively simple pre-filling based on community (PFCI) and pre-filling based on community association (PFCII) are presented to overcome the sparsity. If user-item pair is null, its rating is pre-filling by using our method before traditional collaborative filtering is executed. The experiment shows better performance of our methods.
Keywords :
information filtering; collaborative filtering; data sparseness; e-commerce; prefilling based on community; recommender system; sparsity; user-item pair; Data engineering; Information filtering; Information filters; Information processing; International collaboration; Knowledge engineering; Laboratories; Online Communities/Technical Collaboration; Prediction algorithms; Recommender systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Processing (ISIP), 2008 International Symposiums on
Conference_Location :
Moscow
Print_ISBN :
978-0-7695-3151-9
Type :
conf
DOI :
10.1109/ISIP.2008.68
Filename :
4554054
Link To Document :
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