Issue Date: 10-12 April 2010rnrntOn page(s): rnt165rnttrn- 170rnrnrnLocation: Chicago, IL, USArnrnPrint ISBN: 978-1-4244-6450-0rnrnrnrnttrnDigital Object Identifier: href='http://dx.doi.org/10.1109/ICNSC.2010.5461512' target='_blank'>10.1109/ICNSC.2010.5461512 rnrnDate of Current Version: trnrnt2010-05-06 14:33:13.0rnrnt rntt class="body-text">rntname="Abstract">>Abstractrn>Collaborative Filtering (CF) is the most successful approach of Recommender System. Although it has made significant progress over the last decade, the current CF method is stressed by the sparsity problem. In this paper we propose a novel approach to address this issue. Multiple Imputation (MI) is a useful statistic strategy for dealing with data sets with;
Collaborative Filetring; Mutiple Imputaion; Recommender Systems;
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