Addressing sparse data challenges in recommendation systems: A systematic review of rating estimation using sparse rating data and profile enrichment techniques

E-commerce recommendation systems enhance the user experience by providing customized suggestions tailored to user preferences. They analyze user interactions, such as ratings, to identify user preferences and recommend relevant items accordingly. The sparsity of user–item rating data poses a signif...

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Principais autores:	Thennakoon Mudiyanselage Anupama Udayangani Gunathilaka, Prabhashrini Dhanushika Manage, Jinglan Zhang, Yuefeng Li, Wayne Kelly
Formato:	Artigo
Idioma:	Inglês
Publicado:	Elsevier 2025-03-01
Series:	Intelligent Systems with Applications
Assuntos:	Recommender systems Sparsity challenges Sparse ratings Profile enriching Side information Scalability
Acceso en liña:	http://www.sciencedirect.com/science/article/pii/S2667305324001480
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