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Dialect topic modeling for improved consumer medical search
2010
AMIA Annual Symposium Proceedings
Access to health information by consumers is hampered by a fundamental language gap. Current attempts to close the gap leverage consumer oriented health information, which does not, however, have good coverage of slang medical terminology. In this paper, we present a Bayesian model to automatically align documents with different dialects (slang, common and technical) while extracting their semantic topics. The proposed diaTM model enables effective information retrieval, even when the query
pmid:21346955
pmcid:PMC3041409
fatcat:xnnnmab3c5copobmz5po3u7poa