dc.contributor.author | He, Xiaofen | |
dc.date.accessioned | 2007-01-19 20:48:31 (GMT) | |
dc.date.available | 2007-01-19 20:48:31 (GMT) | |
dc.date.issued | 2007-01-19T20:48:31Z | |
dc.date.submitted | 2007 | |
dc.identifier.uri | http://hdl.handle.net/10012/2663 | |
dc.description.abstract | In order to do more semantics-based information extraction, we require specialized domain models. We develop a hybrid approach for constructing such a domain-specific ontology, which integrates key concepts from the protein-protein–interaction domain with the Gene Ontology. In addition, we present a method for using the domain-specific ontology in a discourse-based analysis module for analyzing full-text articles on protein interactions. The analysis module uses a lexical chaining technique to extract strings of semantically related words that represent the topic structure of the text. We show that the domain-specific ontology improved the performance of the lexical-chaining module. As well the topic structure as represented by the lexical chains contains important information on protein-protein interactions appearing in the same textual context. | en |
dc.format.extent | 1036324 bytes | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | en |
dc.publisher | University of Waterloo | en |
dc.subject | lexical chain ontology construction information extraction | en |
dc.title | A protocol for constructing a domain-specific ontology for use in biomedical information extraction using lexical-chaining analysis | en |
dc.type | Master Thesis | en |
dc.pending | false | en |
dc.subject.program | Computer Science | en |
uws-etd.degree.department | School of Computer Science | en |
uws-etd.degree | Master of Mathematics | en |
uws.typeOfResource | Text | en |
uws.peerReviewStatus | Unreviewed | en |
uws.scholarLevel | Graduate | en |