Computer Science – Computation and Language
Scientific paper
2006-06-28
Proceedings of the Second International Symposium on Semantic Mining in Biomedicine (SMBM 2006) (2006) 60-67
Computer Science
Computation and Language
Scientific paper
We study the adaptation of Link Grammar Parser to the biomedical sublanguage with a focus on domain terms not found in a general parser lexicon. Using two biomedical corpora, we implement and evaluate three approaches to addressing unknown words: automatic lexicon expansion, the use of morphological clues, and disambiguation using a part-of-speech tagger. We evaluate each approach separately for its effect on parsing performance and consider combinations of these approaches. In addition to a 45% increase in parsing efficiency, we find that the best approach, incorporating information from a domain part-of-speech tagger, offers a statistically signicant 10% relative decrease in error. The adapted parser is available under an open-source license at http://www.it.utu.fi/biolg.
Aubin Sophie
Nazarenko Adeline
Pyysalo Sampo
Salakoski Tapio
No associations
LandOfFree
Lexical Adaptation of Link Grammar to the Biomedical Sublanguage: a Comparative Evaluation of Three Approaches does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Lexical Adaptation of Link Grammar to the Biomedical Sublanguage: a Comparative Evaluation of Three Approaches, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Lexical Adaptation of Link Grammar to the Biomedical Sublanguage: a Comparative Evaluation of Three Approaches will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-535177