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- W827141311 abstract "Collaborative filtering approach predicts the preference of active user about specific items transacted on the e-commerce by using others' preference information. To improve the prediction accuracy through collaborative filtering approach, it must be needed to gain enough preference information of users' for predicting preference. But, a bit much information of users' preference might wrongly affect on prediction accuracy, and also too small information of users' preference might make bad effect on the prediction accuracy. This research suggests the method, which decides suitable numbers of neighbor users for applying collaborative filtering algorithm, improved by existing k nearest neighbors selection methods. The result of this research provides useful methods for improving the prediction accuracy and also refines exploratory data analysis approach for deciding appropriate numbers of nearest neighbors." @default.
- W827141311 created "2016-06-24" @default.
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- W827141311 date "2009-01-01" @default.
- W827141311 modified "2023-09-28" @default.
- W827141311 title "A study on neighbor selection methods in k-NN collaborative filtering recommender system" @default.
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