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- W2372891184 abstract "Collaborative filtering is becoming a popular technique for reducing information overload.However,it has three major limitations,accuracy,data sparsity and scalability.We propose a new collaborative filtering algorithm to solve the problem of data sparsity.We utilize the results of singular value decomposition for neighbors selecting,then use the neighborhood-based method to produce the prediction of unrated items.Our experimental results on EachMovie dataset show that the algorithm outperforms the conventional neighborhood-based method and SVD method when the available ratings are sparse." @default.
- W2372891184 created "2016-06-24" @default.
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- W2372891184 date "2006-01-01" @default.
- W2372891184 modified "2023-10-11" @default.
- W2372891184 title "Combining Singular Value Decomposition and Neighbor-based Method in Collaborative Filtering" @default.
- W2372891184 hasPublicationYear "2006" @default.
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