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커뮤니티
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논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국지능시스템학회 INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS INTERNATIONAL JOURNAL of FUZZY LOGIC and INTELLIGENT SYSTEMS Vol.20 No.1
- 발행연도
- 2020.3
- 수록면
- 69 - 76 (8page)
- DOI
- 10.5391/IJFIS.2020.20.1.69
이용수
초록· 키워드
오류제보하기
Named entity recognition and relation extraction are two principal tasks in most natural language processing systems. The majority of methods used in the field implement these two issues independently, thus leading to possible problems such as error propagation from one component (entity detection) to another (relation extraction). To solve such problems, we propose a new architecture for joint identification of entity mentions and their relation by employing a deep neural network framework. The model not only overcomes the error propagation challenge but also improves the detection results of both tasks owing to the cooperation with each other. Experiments on publicly available sources demonstrate that our joint model surpasses competitors in terms of accuracy. The results highlight the improvement achieved by the proposed deep neural network framework for the entity mention and relation classification tasks. Furthermore, we tested the effect of increasing the sentence length and demonstrated its negative influence on the performance.
목차
Abstract
1. Introduction
2. Related Works
3. Proposed Architecture
4. Experiments
5. Conclusion
References
참고문헌 (20)
참고문헌 신청
Bo-Yeong Kang / 2012 / A Muti-Resolution Approach to Restaurant Named Entity Recognition in KoreanWeb / International Journal of Fuzzy Logic and Intelligent systems 12(4):277~284
B. Taskar / 2003 / Max-margin Markov networks / Advances in Neural Information Processing Systems 16:25~32
J. Lafferty / 2001 / Conditional random fields: probabilistic models for segmenting and labeling sequence data / Proceedings of the 18th International Conference on Machine Learning :282~289
I. Tsochantaridis / 2004 / Support vector machine learning for interdependent and structured output spaces / Proceedings of the 21st International Conference on machine Learning :104~112
R. Collobert / 2011 / Natural language processing(almost)from scratch / Journal of Machine Learning Research 12:2493~2537
B. Taskar / 2003 / Max-margin Markov networks / Advances in Neural Information Processing Systems 16:25~32
J. Lafferty / 2001 / Conditional random fields: probabilistic models for segmenting and labeling sequence data / Proceedings of the 18th International Conference on Machine Learning :282~289
I. Tsochantaridis / 2004 / Support vector machine learning for interdependent and structured output spaces / Proceedings of the 21st International Conference on machine Learning :104~112
R. Collobert / 2011 / Natural language processing(almost)from scratch / Journal of Machine Learning Research 12:2493~2537
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UCI(KEPA) : I410-ECN-0101-2020-003-000428694