title: Mining consumer health vocabulary from community-generated text.
abstract: Community-generated text corpora can be a valuable resource to extract consumer health vocabulary (CHV) and link them to professional terminologies and alternative variants. In this research, we propose a pattern-based text-mining approach to identify pairs of CHV and professional terms from Wikipedia, a large text corpus created and maintained by the community. A novel measure, leveraging the ratio of frequency of occurrence, was used to differentiate consumer terms from professional terms. We empirically evaluated the applicability of this approach using a large data sample consisting of MedLine abstracts and all posts from an online health forum, MedHelp. The results show that the proposed approach is able to identify synonymous pairs and label the terms as either consumer or professional term with high accuracy. We conclude that the proposed approach provides great potential to produce a high quality CHV to improve the performance of computational applications in processing consumer-generated health text.
authors.affiliation: School of Information, University of Michigan, Ann Arbor, MI.
authors.forename: V G Vinod
authors.initials: VG
authors.lastname: Vydiswaran
authors.affiliation: School of Information, University of Michigan, Ann Arbor, MI ; Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI.
authors.forename: Qiaozhu
authors.initials: Q
authors.lastname: Mei
authors.affiliation: Department of Pediatrics, University of Michigan, Ann Arbor, MI ; School of Information, University of Michigan, Ann Arbor, MI.
authors.forename: David A
authors.initials: DA
authors.lastname: Hanauer
authors.affiliation: School of Public Health Department of Health Management and Policy, University of Michigan, Ann Arbor, MI ; School of Information, University of Michigan, Ann Arbor, MI.
authors.forename: Kai
authors.initials: K
authors.lastname: Zheng
mesh_terms: D054626:Consumer Health Information; D057225:Data Mining; D004690:Encyclopedias as Topic; D020407:Internet; D009626:Terminology as Topic; D014825:Vocabulary