Optimizing Latent Factors and Collaborative Filtering for Students’ Performance Prediction

Optimizing Latent Factors and Collaborative Filtering for Students’ Performance Prediction

The problem of predicting students’ performance has been recently tackled by using matrix factorization, a popular method applied for collaborative filtering based recommender systems. This problem consists of predicting the unknown performance or score of a particular student for a task s/he did no...

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Bibliographic Details
Main Authors:	Juan A. Gómez-Pulido, Arturo Durán-Domínguez, Francisco Pajuelo-Holguera
Format:	Article
Language:	English
Published:	MDPI AG 2020-08-01
Series:	Applied Sciences
Subjects:	recommender systems collaborative filtering matrix factorization gradient descent latent factors learning rate
Online Access:	https://www.mdpi.com/2076-3417/10/16/5601

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