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...

Volledige beschrijving

Bewaard in:

Bibliografische gegevens
Hoofdauteurs:	Sofia-Anna Lapadaki, John Nanos, Dionisis Margaris, Costas Vassilakis, Dimitris Spiliotopoulos
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	MDPI AG 2026-02-01
Reeks:	Future Internet
Onderwerpen:	collaborative filtering rating prediction sparse datasets recommender systems K-nearest neighbors (KNN) prediction accuracy
Online toegang:	https://www.mdpi.com/1999-5903/18/2/114
Tags:	Voeg label toe Geen labels, Wees de eerste die dit record labelt!

Optimizing Collaborative Filtering for Accurate Rating Predictions in Very Sparse Datasets

Gelijkaardige items