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

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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Bibliographic Details
Main Authors: Thennakoon Mudiyanselage Anupama Udayangani Gunathilaka, Prabhashrini Dhanushika Manage, Jinglan Zhang, Yuefeng Li, Wayne Kelly
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Intelligent Systems with Applications
Subjects:
Recommender systems
Sparsity challenges
Sparse ratings
Profile enriching
Side information
Scalability
Online Access:http://www.sciencedirect.com/science/article/pii/S2667305324001480
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