On Exploiting Rating Prediction Accuracy Features in Dense Collaborative Filtering Datasets

On Exploiting Rating Prediction Accuracy Features in Dense Collaborative Filtering Datasets

One of the typical goals of collaborative filtering algorithms is to produce rating predictions with values very close to what real users would give to an item. Afterward, the items having the largest rating prediction values will be recommended to the users by the recommender system. Collaborative...

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Bibliographic Details
Main Authors: Dimitris Spiliotopoulos, Dionisis Margaris, Costas Vassilakis
Format: Article
Language:English
Published: MDPI AG 2022-09-01
Series:Information
Subjects:
collaborative filtering
recommender systems
personalisation
dataset density
rating prediction accuracy
accuracy features
Online Access:https://www.mdpi.com/2078-2489/13/9/428

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https://www.mdpi.com/2078-2489/13/9/428

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