Abstract
The language gap existing between health consumers and health professionals hinders effective healthcare information retrieval and communication. To bridge this language gap, many efforts have been taken to develop the Consumer Health Vocabularies (CHVs). One crucial task in developing CHVs is extracting consumer health expressions. However, most of existing studies of consumer health expressions extraction involve heavy human efforts. In this work, we presented automatic methods based on co-occurrence analysis for extracting consumer health expressions from consumer-contributed content in social media data. The experiment results showed that our proposed methods are effective.
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© 2015 Springer International Publishing Switzerland
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Jiang, L., Yang, C.C. (2015). Expanding Consumer Health Vocabularies by Learning Consumer Health Expressions from Online Health Social Media. In: Agarwal, N., Xu, K., Osgood, N. (eds) Social Computing, Behavioral-Cultural Modeling, and Prediction. SBP 2015. Lecture Notes in Computer Science(), vol 9021. Springer, Cham. https://doi.org/10.1007/978-3-319-16268-3_36
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DOI: https://doi.org/10.1007/978-3-319-16268-3_36
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