DocumentCode
3073101
Title
A Hybrid Collaborative Filtering Recommendation Algorithm for Solving the Data Sparsity
Author
He, Ying ; Yang, Shaoyu ; Jiao, Chenbin
Author_Institution
Henan Bus. Coll., Zhengzhou, China
fYear
2011
fDate
16-17 July 2011
Firstpage
118
Lastpage
121
Abstract
With the huge electronic data´s explosion in the commercial and the service area, the collaborative filtering technology attracts many of researchers´ attention. In this paper, we provide a hybrid collaborative filtering recommendation algorithm, which based on the research and analyses for the data sparsity and the similarity accuracy. The simulation result indicates that the algorism can solve effectively the extreme data sparsity and promote the similarity accuracy in collaborative filtering.
Keywords
data handling; information filtering; recommender systems; data sparsity; electronic data explosion; hybrid collaborative filtering recommendation algorithm; Accuracy; Bayesian methods; Collaboration; Data models; Filling; Filtering; Predictive models; collaborative filtering algorism [CFA]; data sparsity; recommend system [RS];
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Society (ISCCS), 2011 International Symposium on
Conference_Location
Kota Kinabalu
Print_ISBN
978-1-4577-0644-8
Type
conf
DOI
10.1109/ISCCS.2011.40
Filename
6004281
Link To Document