2006 ExploitingShallowLingInfForRelExtrInBiomedLit

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Subject Headings: Supervised Relation Recognition Algorithm, Shallow Linguistic Feature

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Abstract

  • We propose an approach for extracting relations between entities from biomedical literature based solely on shallow linguistic information. We use a combination of kernel functions to integrate two different information sources: (i) the whole sentence where the relation appears, and (ii) the local contexts around the interacting entities. We performed experiments on extracting gene and protein interactions from two different data sets. The results show that our approach outperforms most of the previous methods based on syntactic and semantic information. 1,


 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2006 ExploitingShallowLingInfForRelExtrInBiomedLitClaudio Giuliano
Alberto Lavelli
Lorenza Romano
Exploiting Shallow Linguistic Information for Relation Extraction from Biomedical LiteratureProceedings of the 11th Conference of the European Chapter of the Association for Computational Linguisticshttp://acl.ldc.upenn.edu/E/E06/E06-1051.pdf2006