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
Authors

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.