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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제11권 제2호
- 발행연도
- 2015.1
- 수록면
- 248 - 265 (18page)
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초록· 키워드
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In this paper, we propose a maximum entropy-based model, which can mathematically explain the biomolecular event extraction problem. The proposed model generates an event table, which can represent the relationship between an event trigger and its arguments. The complex sentences with distinctive event structures can be also represented by the event table. Previous approaches intuitively designed a pipeline system, which sequentially performs trigger detection and arguments recognition, and thus, did not clearly explain the relationship between identified triggers and arguments. On the other hand, the proposed model generates an event table that can represent triggers, their arguments, and their relationships. The desired events can be easily extracted from the event table. Experimental results show that the proposed model can cover 91.36% of events in the training dataset and that it can achieve a 50.44% recall in the test dataset by using the event table.
목차
등록된 정보가 없습니다.
참고문헌 (22)
참고문헌 신청
A. Airola / 2008 / All-Paths Graph Kernel for Protein-Protein Interaction Extraction with Evaluation of Cross-corpus Learning / BMC Bioinformatics 9 (Suppl. 11)
A. L. Berger / 1996 / A maximum entropy approach to natural language processing / Computational Linguistics 22 (1) : 3
A. Vlachos / 2009 / Biomedical event extraction without training data / Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task : 37 ~ 40
C. Blaschke / 1999 / "Automatic extraction of biological information from scientific text: protein-protein interactions / Proceedings of International Conference on Intelligent Sys
E. Buyko / 2011 / Syntactic simplification and semantic enrichment-trimming dependency graphs for event extraction / Computational Intelligence 27 (4) : 610 ~ 644
A. L. Berger / 1996 / A maximum entropy approach to natural language processing / Computational Linguistics 22 (1) : 3
A. Vlachos / 2009 / Biomedical event extraction without training data / Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task : 37 ~ 40
C. Blaschke / 1999 / "Automatic extraction of biological information from scientific text: protein-protein interactions / Proceedings of International Conference on Intelligent Sys
E. Buyko / 2011 / Syntactic simplification and semantic enrichment-trimming dependency graphs for event extraction / Computational Intelligence 27 (4) : 610 ~ 644
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