Paper: Improving Summarization of Biomedical Documents Using Word Sense Disambiguation

ACL ID W10-1907
Title Improving Summarization of Biomedical Documents Using Word Sense Disambiguation
Venue Workshop on Biomedical Natural Language Processing
Session
Year 2010
Authors

We describe a concept-based summariza- tion system for biomedical documents and show that its performance can be improved using Word Sense Disambiguation. The system represents the documents as graphs formed from concepts and relations from the UMLS. A degree-based clustering al- gorithm is applied to these graphs to dis- cover different themes or topics within the document. To create the graphs, the MetaMap program is used to map the text onto concepts in the UMLS Metathe- saurus. This paper shows that applying a graph-based Word Sense Disambiguation algorithm to the output of MetaMap im- proves the quality of the summaries that are generated.