Online health community recommendation System with LDA-FCM approach

Shan, S ORCID: https://orcid.org/0000-0003-4928-588X, Farooq, U, Wang, JL, Li, YL and Gümüş, DB, 2025. Online health community recommendation System with LDA-FCM approach. Engineering Headway, 27, pp. 329-342. ISSN 2813-8333

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Abstract

Online health communities generate vast knowledge on various topics, making it challenging to track latent themes and correlations among key variables. Identifying these hidden variables and their relationships can enhance user engagement and content curation. This paper introduces a novel approach using fuzzy cognitive maps to uncover these variables and causal relationships in online health communities, providing users with valuable insights for disease management and treatment. The study employed Latent Dirichlet Allocation (LDA) to generate topics from an online health forum, using this as evidence to construct fuzzy cognitive maps. The proposed system reflects disease development and offers significant insights for managing health conditions. The findings have theoretical and practical implications for developing online recommendation systems in the healthcare domain. This study contributes to the literature by proposing a method for identifying key variables and relationships, aiding health professionals and patients in understanding and managing health conditions. Future research will explore the system’s effectiveness in real-world settings and the role of user-generated content in enhancing recommendation systems.

Item Type:	Journal article
Description:	Paper presented at The 10th International Conference on Science and Technology, Yogyakarta, Indonesia, 23-24 October 2024
Publication Title:	Engineering Headway
Creators:	Shan, S., Farooq, U., Wang, J.L., Li, Y.L. and Gümüş, D.B.
Date:	13 October 2025
Volume:	27
ISSN:	2813-8333
Identifiers:	Number Type 10.4028/v-zm6skq DOI 2521932 Other
Divisions:	Schools > Nottingham Business School
Record created by:	Jeremy Silvester
Date Added:	21 Nov 2025 09:25
Last Modified:	21 Nov 2025 09:25
URI:	https://irep.ntu.ac.uk/id/eprint/54789

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