The Recommendation Algorithm Based on Improved Conditional Variational Autoencoder and Constrained Probabilistic Matrix Factorization

An improved recommendation algorithm based on Conditional Variational Autoencoder (CVAE) and Constrained Probabilistic Matrix Factorization (CPMF) is proposed to address the issues of poor recommendation performance in traditional user-based collaborative filtering algorithms caused by data sparsity...

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Bibliographic Details

Published in:	Applied sciences Vol. 13; no. 21; p. 12027
Main Authors:	Zhang, Yunfei, Xu, Hongzhen, Yu, Xiaojun
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.11.2023
Subjects:	Algorithms Analysis auxiliary information Collaboration collaborative filtering conditional variational autoencoder constrained probabilistic matrix factorization feature matric Neural networks Optimization techniques Ratings & rankings Recommender systems Sparsity User behavior New York
ISSN:	2076-3417, 2076-3417
Online Access:	Get full text
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