Cross-domain information fusion and personalized recommendation in artificial intelligence recommendation system based on mathematical matrix decomposition

Given the challenges of inter-domain information fusion and data sparsity in collaborative filtering algorithms, this paper proposes a cross-domain information fusion matrix decomposition algorithm to enhance the accuracy of personalized recommendations in artificial intelligence recommendation syst...

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Vydané v:	Scientific reports Ročník 14; číslo 1; s. 7816 - 13
Hlavný autor:	Meng, Xiaoyan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 03.04.2024 Nature Publishing Group Nature Portfolio
Predmet:	639/705 639/705/1041 639/705/1042 639/705/117 639/705/258 Accuracy Algorithms Artificial intelligence Collaboration Collaborative filtering algorithm Cross-domain information fusion Data sparsity Decomposition Humanities and Social Sciences Information processing Least squares method Mathematical models Matrix factorization algorithm multidisciplinary Personalized recommendation Recommender systems Regularization methods Science Science (multidisciplinary) Social organization Personalized recommendation Collaborative filtering algorithm Cross-domain information fusion Data sparsity Matrix factorization algorithm
ISSN:	2045-2322, 2045-2322
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