教師資料查詢 | 類別: 期刊論文 | 教師: 張瑋倫 Chang Wei-lun (瀏覽個人網頁)

標題:An Ordinal Regression Model with SVD Hebbian Learning for Collaborative Recommendation
學年102
學期2
出版(發表)日期2014/03/01
作品名稱An Ordinal Regression Model with SVD Hebbian Learning for Collaborative Recommendation
作品名稱(其他語言)
著者Chang, Te-Min; Hsiao, Wen-Feng; Chang, Wei-Lun
單位淡江大學企業管理學系
出版者Taipei: Institute of Information Science
著錄名稱、卷期、頁數Journal of Information Science and Engineering 30(2), pp.387-401
摘要The Internet is disseminating more and more information as it continues to grow. This large amount of information, however, can cause an information overload problem for users. Recommender systems to help predict user preferences for new information can ease users’ mental loads. The model-based collaborative filtering (CF) approach and its variants for recommender systems have recently received considerable attention. Nonetheless, two issues should be carefully considered in practical applications. First, the data reliability of the rating matrix can affect the prediction performance. Second, most current models view the measurement scale of output classes as nominal instead of ordinal ratings. This study proposes a model-based CF approach that deals with both issues. Specifically, this approach uses the Hebbian learning rule to facilitate singular value decomposition in reducing noisy and redundant data, and employs support vector ordinal regression to build up the models. The results of the experiments conducted in this study show that the proposed approach outperforms other methods, especially under data of mild data sparsity and large-scale conditions. The feasibility of the proposed approach is justified accordingly.
關鍵字recommender systems;collaborative filtering;model-based CF;data reliability;ordinal scale
語言英文(美國)
ISSN1016-2364
期刊性質國內
收錄於SCI;
產學合作
通訊作者
審稿制度
國別中華民國
公開徵稿
出版型式,紙本
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