Comprehensive Review of Meta-Learning Methods for Cold-Start Issue in Recommendation Systems

Comprehensive Review of Meta-Learning Methods for Cold-Start Issue in Recommendation Systems

The cold-start issue in recommendation systems refers to the challenge of recommending items or users when minimal or no prior data is available. Meta-learning methods have emerged as a response to this challenge due to their ability to transfer prior knowledge to recommendation tasks. However, meta...

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Bibliographic Details
Main Authors: Jamallah M. Zawia, Maizatul Akmar Binti Ismail, Mohammad Imran, Buce Trias Hanggara, Diva Kurnianingtyas, Silvi Asna, Quang Tran Minh
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Recommendation systems
cold-start
meta-learning
systematic review
strengths and limitations
Online Access:https://ieeexplore.ieee.org/document/10857336/
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