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Enriching Consumer Health Vocabulary Through Mining A Social Q&a Site

Title: Enriching Consumer Health Vocabulary Through Mining A Social Q&a Site: A Similarity-based Approach.
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Name(s): He, Zhe, author
Chen, Zhiwei, author
Oh, Sanghee, author
Hou, Jinghui, author
Bian, Jiang, author
Type of Resource: text
Genre: Journal Article
Text
Journal Article
Date Issued: 2017-05
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: The widely known vocabulary gap between health consumers and healthcare professionals hinders information seeking and health dialogue of consumers on end-user health applications. The Open Access and Collaborative Consumer Health Vocabulary (OAC CHV), which contains health-related terms used by lay consumers, has been created to bridge such a gap. Specifically, the OAC CHV facilitates consumers' health information retrieval by enabling consumer-facing health applications to translate between professional language and consumer friendly language. To keep up with the constantly evolving medical knowledge and language use, new terms need to be identified and added to the OAC CHV. User-generated content on social media, including social question and answer (social Q&A) sites, afford us an enormous opportunity in mining consumer health terms. Existing methods of identifying new consumer terms from text typically use ad-hoc lexical syntactic patterns and human review. Our study extends an existing method by extracting n-grams from a social Q&A textual corpus and representing them with a rich set of contextual and syntactic features. Using K-means clustering, our method, simiTerm, was able to identify terms that are both contextually and syntactically similar to the existing OAC CHV terms. We tested our method on social Q&A corpora on two disease domains: diabetes and cancer. Our method outperformed three baseline ranking methods. A post-hoc qualitative evaluation by human experts further validated that our method can effectively identify meaningful new consumer terms on social Q&A. (C) 2017 Elsevier Inc. All rights reserved.
Identifier: FSU_libsubv1_wos_000409395900008 (IID), 10.1016/j.jbi.2017.03.016 (DOI)
Keywords: information, Consumer health information, Consumer health vocabulary, Controlled vocabularies, knowledge, Ontology enrichment, records, Social Q&A, text
Publication Note: The publisher's version of record is available at https://doi.org/10.1016/j.jbi.2017.03.016
Persistent Link to This Record: http://purl.flvc.org/fsu/fd/FSU_libsubv1_wos_000409395900008
Owner Institution: FSU
Is Part Of: Journal of Biomedical Informatics.
1532-0464
Issue: vol. 69

Choose the citation style.
He, Z., Chen, Z., Oh, S., Hou, J., & Bian, J. (2017). Enriching Consumer Health Vocabulary Through Mining A Social Q&a Site: A Similarity-based Approach. Journal Of Biomedical Informatics. Retrieved from http://purl.flvc.org/fsu/fd/FSU_libsubv1_wos_000409395900008