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- W2383735400 abstract "To overcome several limitations in the research area of collaborative filtering(CF),this paper presents a CF recommendation algorithm,named UNCF(Uncertain Neighbors' Collaborative Filtering Recommendation Algorithm).In the reality,the scene of recommendation is uncertain.The similarities computations of both user-based and item-based are considered to choose the neighbors dynamically as the recommendation set.This set can be used to select the trustworthy subset which is the most effective objects to the predicted result.Moreover,this paper defines a new prediction algorithm that combines the advantages of trustworthy subset for this uncertain recommendation method.Through experimental results,the UNCF algorithm can consistently achieve better prediction accuracy than traditional CF algorithms,and effectively leverage the result in the uncertain environment.Furthermore,the algorithm can alleviate the dataset sparsity problem." @default.
- W2383735400 created "2016-06-24" @default.
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- W2383735400 date "2010-01-01" @default.
- W2383735400 modified "2023-09-25" @default.
- W2383735400 title "Uncertain Neighbors' Collaborative Filtering Recommendation Algorithm" @default.
- W2383735400 hasPublicationYear "2010" @default.
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