Optimizing Collaborative Filtering for Accurate Rating Predictions in Very Sparse Datasets

Collaborative filtering is one of the most widely used methods for user rating prediction in recommender systems. To evaluate a collaborative filtering system, rating datasets are typically used, which comprise thousands to millions of records consisting of user–item–rating tuples. Initially, a simi...

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Bibliografiske detaljer

Principais autores:	Sofia-Anna Lapadaki, John Nanos, Dionisis Margaris, Costas Vassilakis, Dimitris Spiliotopoulos
Format:	Artigo
Sprog:	Inglês
Udgivet:	MDPI AG 2026-02-01
Serier:	Future Internet
Fag:	collaborative filtering rating prediction sparse datasets recommender systems K-nearest neighbors (KNN) prediction accuracy
Online adgang:	https://www.mdpi.com/1999-5903/18/2/114
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