Paper: Lexical Substitution for the Medical Domain

ACL ID D14-1066
Title Lexical Substitution for the Medical Domain
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2014

In this paper we examine the lexical substitu- tion task for the medical domain. We adapt the current best system from the open domain, which trains a single classifier for all instances using delexicalized features. We show sig- nificant improvements over a strong baseline coming from a distributional thesaurus (DT). Whereas in the open domain system, features derived from WordNet show only slight im- provements, we show that its counterpart for the medical domain (UMLS) shows a signif- icant additional benefit when used for feature generation.