Citation

Haw, Su Cheng and Jayaram, Jayapradha and Anaam, Elham Abdulwahab and Santoso, Heru Agus Exploring Recommender Systems in the Healthcare: A Review on Methods, Applications and Evaluations. International Journal on Robotics, Automation and Sciences, 6 (2). ISSN 2682-860X

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Abstract

Due to the vast amount of publicly available online data, people may find it difficult to obtain relevant information to find food or meals that match their taste and health while maintaining a healthy lifestyle. The overload of information makes it difficult to separate relevant, personalized information from massive volumes of data. Recommendation systems (RS) are suggestion system that provides users with information that they may be interested in. With RS, this enormous amount of information is filtered and analyzed for further insights. This paper will explore several generations of recommender systems in the healthcare industry. This paper offers a thorough analysis of the current state-of-the-art recommender systems focusing on the grouping, methods, application and evaluation metrics. In addition, several challenges for further research and improvement in this domain are also outlined in the paper.

Item Type:	Article
Uncontrolled Keywords:	Recommender System, Recommendation Technique, Evaluation, Traditional Recommender System, Generative AI
Subjects:	H Social Sciences > HD Industries. Land use. Labor > HD28-70 Management. Industrial Management > HD30.2 Electronic data processing. Information technology. Including artificial intelligence and knowledge management
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	11 Jul 2025 03:20
Last Modified:	11 Jul 2025 03:20
URII:	http://shdl.mmu.edu.my/id/eprint/14266

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