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Open AccessArticle

Knowledge Discovery from Posts in Online Health Communities Using Unified Medical Language System

1
Department of Information Management, School of Economics and Management, Beijing Jiaotong University, Beijing 100044, China
2
Henley Business School, University of Reading, Reading RG6 6UD, UK
*
Author to whom correspondence should be addressed.
Int. J. Environ. Res. Public Health 2018, 15(6), 1291; https://doi.org/10.3390/ijerph15061291
Received: 31 May 2018 / Revised: 15 June 2018 / Accepted: 16 June 2018 / Published: 19 June 2018
Patient-reported posts in Online Health Communities (OHCs) contain various valuable information that can help establish knowledge-based online support for online patients. However, utilizing these reports to improve online patient services in the absence of appropriate medical and healthcare expert knowledge is difficult. Thus, we propose a comprehensive knowledge discovery method that is based on the Unified Medical Language System for the analysis of narrative posts in OHCs. First, we propose a domain-knowledge support framework for OHCs to provide a basis for post analysis. Second, we develop a Knowledge-Involved Topic Modeling (KI-TM) method to extract and expand explicit knowledge within the text. We propose four metrics, namely, explicit knowledge rate, latent knowledge rate, knowledge correlation rate, and perplexity, for the evaluation of the KI-TM method. Our experimental results indicate that our proposed method outperforms existing methods in terms of providing knowledge support. Our method enhances knowledge support for online patients and can help develop intelligent OHCs in the future. View Full-Text
Keywords: online posts; online health communities; knowledge discovery; Unified Medical Language System; text mining online posts; online health communities; knowledge discovery; Unified Medical Language System; text mining
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Chen, D.; Zhang, R.; Liu, K.; Hou, L. Knowledge Discovery from Posts in Online Health Communities Using Unified Medical Language System. Int. J. Environ. Res. Public Health 2018, 15, 1291.

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