Feifan Liu|Lamont Antieau|Hong Yu
Toward automated consumer question answering: Automatically separating consumer questions from professional questions in the healthcare domain
University of Wisconsin–Milwaukee|University of Wisconsin–Milwaukee|University of Wisconsin–Milwaukee
healthcare professionals healthcare consumers information needs met use computers specifically via medical question answering systems however information needs groups different terms literacy levels technical expertise effective question answering system must able account differences formulate relevant responses users group paper propose first step toward answering queries different users automatically classifying questions according whether asked healthcare professionals consumers obtained two sets consumer questions 10000 questions total yahoo answers professional questions consist two question collections 4654 pointofcare questions denoted pointcare obtained interviews group family doctors following patient visits 5378 questions physician practices professional online services denoted onlinepractice 20000 questions combined developed supervised machinelearning models automatic classification consumer questions professional questions evaluate robustness models tested model trained consumerpointcare dataset consumeronlinepractice dataset evaluated linguistic features statistical features examined characteristics two different types professional questions pointcare vs onlinepractice may affect classification performance explored information gain feature reduction backoff linguistic category features 10fold crossvalidation results showed best f1measure 0936 0946 consumerpointcare consumeronlinepractice respectively best f1measure 0891 testing consumerpointcare model consumeronlinepractice dataset healthcare consumer questions posted yahoo online communities reliably classified professional questions posted pointofcare clinicians online physicians supervised machinelearning models robust task study significantly benefit development automated consumer question answering