DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ming Cheng | ko |
dc.contributor.author | 이도헌 | ko |
dc.date.accessioned | 2013-03-06T08:13:20Z | - |
dc.date.available | 2013-03-06T08:13:20Z | - |
dc.date.created | 2012-02-06 | - |
dc.date.created | 2012-02-06 | - |
dc.date.issued | 2006-12 | - |
dc.identifier.citation | BIOINFORMATICS AND BIOSYSTEMS, v.1, no.3, pp.221 - 225 | - |
dc.identifier.issn | 1738-9798 | - |
dc.identifier.uri | http://hdl.handle.net/10203/86404 | - |
dc.description.abstract | Scientific literature is the most reliable and comprehensive source of knowledge about molecular interaction networks. This knowledge is scattered in scientific literature written in natural languages, much time and labor have to be spent on manually extracting biological molecule interactions from literature. There have been many efforts for automatic extraction of biomedical knowledge from literatures. We propose a pattern matching algorithm with multiple Part-Of-Speech tagging based rules which could effectively reduce the required number of patterns and increase the recovery rate of traditional pattern matching algorithm. Various situations in biomedical texts are studied in the paper. The recovery and accuracy rate of the system is estimated to be 68.7% and 93.0%, respectively. | - |
dc.language | English | - |
dc.publisher | 한국생물정보시스템생물학회 | - |
dc.title | A Rule-Based Approach Toward Extraction of Interaction Information from Scientific Literature | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.citation.volume | 1 | - |
dc.citation.issue | 3 | - |
dc.citation.beginningpage | 221 | - |
dc.citation.endingpage | 225 | - |
dc.citation.publicationname | BIOINFORMATICS AND BIOSYSTEMS | - |
dc.contributor.localauthor | 이도헌 | - |
dc.contributor.nonIdAuthor | Ming Cheng | - |
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