Joint entity and relation extraction with position-aware attention and relation embedding
Author:
Funder
National Defense Basic Scientific Research Program of China
Publisher
Elsevier BV
Subject
Software
Reference55 articles.
1. Relation classification via keyword-attentive sentence mechanism and synthetic stimulation loss;Li;IEEE/ACM Trans. Audio Speech Lang. Process.,2019
2. A review of relational machine learning for knowledge graphs;Nickel;Proc. IEEE,2015
3. Y.K. Lin, Z.Y. Liu, M.S. Sun, Y. Liu, X. Zhu, Learning entity and relation embeddings for knowledge graph completion, in: Proc. Twenty-Ninth AAAI Conf. Artif. Intel, 2015, pp. 2181–2187.
4. C. Shi, S. Liu, S. Ren, S. Feng, M. Li, M. Zhou, H. Wang, Knowledge-based semantic embedding for machine translation, in: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2016, pp. 2245–2254.
5. R. Das, M. Zaheer, S. Reddy, A. McCallum, Question answering on knowledge bases and text using universal schema and memory networks, in: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2017, pp. 358–365.
Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Multi-View Cooperative Learning with Invariant Rationale for Document-Level Relation Extraction;Cognitive Computation;2024-07-27
2. Joint entity and relation extraction combined with multi-module feature information enhancement;Complex & Intelligent Systems;2024-06-16
3. Dependency-position relation graph convolutional network with hierarchical attention mechanism for relation extraction;The Journal of Supercomputing;2024-05-24
4. ParTRE: A relational triple extraction model of complicated entities and imbalanced relations in Parkinson’s disease;Journal of Biomedical Informatics;2024-04
5. Combining Sentence-based Relational Features with Biaffine Mechanism for Triple Extraction;Proceedings of the 2024 16th International Conference on Machine Learning and Computing;2024-02-02
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3