[1]张勇,高大林,巩敦卫,等.用于关系抽取的注意力图长短时记忆神经网络[J].智能系统学报,2021,16(3):518-527.[doi:10.11992/tis.202008036]
 ZHANG Yong,GAO Dalin,GONG Dunwei,et al.Attention graph long short-term memory neural network for relation extraction[J].CAAI Transactions on Intelligent Systems,2021,16(3):518-527.[doi:10.11992/tis.202008036]
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用于关系抽取的注意力图长短时记忆神经网络

参考文献/References:
[1] 杨志豪,洪莉,林鸿飞,等. 基于支持向量机的生物医学文献蛋白质关系抽取[J]. 智能系统学报, 2008(4):361-369
Yang Zhihao, Hong Li, Lin Hongfei, et al. Extraction of information on protein-protein interaction from biomedical literatures using an SVM[J]. CAAI transactions on intelligent systems, 2008(4):361-369
[2] 李智超. 图文知识图谱中的关系抽取算法研究[D]. 北京:北京邮电大学, 2018.
LI Zhichao. A relation extraction algorithm in multi-modal knowledge graph[D]. Beijing:Beijing University of Posts and Telecommunications, 2018.
[3] 张涛,贾真,李天瑞,等. 基于知识库的开放领域问答系统[J]. 智能系统学报, 2018, 13(4):557-563
ZHANG Tao, JIA Zhen, LI Tianrui, et al. Open-domain question-answering system based on large-scale knowledge base[J]. CAAI transactions on intelligent systems, 2018, 13(4):557-563
[4] ZHOU Peng, SHI Wei, TIAN Jun, et al. Attention-based bidirectional long short-term memory networks for relation classification[C]//Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics. Berlin, Germany:Association for Computational Linguistics, 2016:207-212.
[5] ZHANG Lei, XIANG Fusheng. Relation classification via BiLSTM-CNN[C]//Proceedings of the 3rd International Conference on Data Mining and Big Data. Shanghai, China:Springer, 2018:373-382.
[6] XU Yan, MOU Lili, LI Ge, et al. Classifying relations via long short term memory networks along shortest dependency paths[C]//Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing. Lisbon, Portugal:Association for Computational Linguistics, 2015:1785-1794.
[7] TAI K S, SOCHER R, MANNING C D. Improved semantic representations from tree-structured long short-Term memory networks[C]//Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing. Beijing, China:Association for Computational Linguistics, 2015:1556-1566.
[8] ZHANG Yuhao, QI Peng, MANNING C D. Graph convolution over pruned dependency trees improves relation extraction[C]//Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Brussels, Belgium:Association for Computational Linguistics, 2018:2205-2215.
[9] 甘丽新, 万常选, 刘德喜, 等. 基于句法语义特征的中文实体关系抽取[J]. 计算机研究与发展, 2016, 53(2):284-302
GAN Lixin, WANG Changxuan, LIU Dexi, et al. Chinese named entity relation extraction based on syntactic and semantic features[J]. Journal of computer research and development, 2016, 53(2):284-302
[10] GUO Zhijiang, ZHANG Yan, LU Wei. Attention guided graph convolutional networks for relation extraction[C]//Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Florence, Italy:ACL, 241-251.
[11] FU T J, LI P H, MA Weiyun. GraphRel:modeling text as relational graphs for joint entity and relation extraction[C]//Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Florence, Italy:Association for Computational Linguistics, 2019:1409-1418.
[12] PENG Nanyun, POON H, QUIRK C, et al. Cross-sentence N-ary relation extraction with graph LSTMs[J]. Transactions of the association for computational linguistics, 2017, 5:101-115.
[13] SONG Linfeng, ZHANG Yue, WANG Zhiguo, et al. N-ary relation extraction using graph state LSTM[C]//Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. Brussels, Belgium:Association for Computational Linguistics, 2018:2226-2235.
[14] ZHOU Peng, XU Jiaming, QI Zhenyu, et al. Distant supervision for relation extraction with hierarchical selective attention[J]. Neural networks, 2018, 108:240-247.
[15] JI Guoliang, LIU Kang, HE Shizhu, et al. Distant supervision for relation extraction with sentence-level attention and entity descriptions[C]//Proceedings of the 31st AAAI Conference on Artificial Intelligence. San Francisco, USA:AAAI Press, 2017.
[16] ZHANG Shu, ZHENG Dequan, HU Xinchen, et al. Bidirectional long short-term memory networks for relation classification[C]//Proceedings of the 29th Pacific Asia Conference on Language, Information and Computation. Shanghai, China:PACLIC, 2015:73-78.
[17] ZELENKO D, AONE C, RICHARDELLA A. Kernel methods for relation extraction[J]. The journal of machine learning research, 2003, 3:1083-1106.
[18] ZENG Daojian, LIU Kang, LAI Siwei, et al. Relation classification via convolutional deep neural network[C]//Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics:Technical Papers. Dublin, Ireland:Dublin City University and Association for Computational Linguistics, 2014:2335-2344.
[19] ZHANG Yuhao, ZHONG V, CHEN Danqi, et al. Position-aware attention and supervised data improve slot filling[C]//Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Copenhagen, Denmark:Association for Computational Linguistics, 2017:35-45.
[20] 马语丹, 赵义, 金婧, 等. 结合实体共现信息与句子语义特征的关系抽取方法[J]. 中国科学:信息科学, 2018, 48(11):1533-1545
MA Yudan, ZHAO Yi, JIN Jing, et al. Combining entity co-occurrence information and sentence semantic features for relation extraction[J]. Scientia sinica informationis, 2018, 48(11):1533-1545
[21] MINTZ M, BILLS S, SNOW R, et al. Distant supervision for relation extraction without labeled data[C]//Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP. Suntec, Singapore:Association for Computational Linguistics, 2009:1003-1011.
[22] ZENG D, KANG L, CHEN Y, et al. Distant supervision for relation extraction via piecewise convolutional neural networks[C]//Proceedings of the Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processin. Lisbon, Portugal, 2015:1753-1762.
[23] HENDRICKX I, KIM S N, KOZAREVA Z, et al. Semeval-2010 task 8:Multi-way classification of semantic relations between pairs of nominals[C]//Proceedings of the 5th International Workshop on Semantic Evaluation. Uppsala, Sweden:ACM, 2010:33-38.
[24] PENNINGTON J, SOCHER R, MANNING C. GloVe:global vectors for word representation[C]//Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing. Doha, Qatar:Association for Computational Linguistics, 2014:1532-1543.
[25] YU Bowen, ZHANG Zhenyu, LIU Tingwen, et al. Beyond word attention:using segment attention in neural relation extraction[C]//Proceedings of the 28th International Joint Conference on Artificial Intelligence. Macao, China:IJCAI, 2019:33-38.
[26] LEE J, SEO S, CHOI Y S. Semantic relation classification via bidirectional LSTM networks with entity-aware attention using latent entity typing[J]. Symmetry, 2019, 11(6):785.
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备注/Memo

收稿日期:2020-08-30。
基金项目:国家重点研发计划项目(2020YFB1708200);科技部科技创新2030重大项目(2020AAA0107300)
作者简介:张勇,教授,博士生导师,博士,中国人工智能学会自然计算与数字智能城市专委会委员,主要研究方向为智能优化和数据挖掘。主持国家自然科学基金3项,中国博士后科学基金特别资助等省部级科研项目5项。获教育部高等学校科学研究优秀成果二等奖。获授权发明专利4项,发表学术论文50余篇;高大林,硕士研究生,主要研究方向为自然语言处理、关系抽取;巩敦卫,教授,博士生导师,博士,江苏省自动化学会常务理事、副秘书长,主要研究方向为智能优化和软件测试。主持国家“973”计划子课题1项,国家重点研发计划子课题1项,国家自然科学基金6项,省部级科研项目8项。获高等学校科学研究优秀成果二等奖、江苏省科学技术二等奖。获授权发明专利15项。出版专著8部,发表学术论文100余篇
通讯作者:高大林.E-mail:1367963012@qq.com

更新日期/Last Update: 2021-06-25
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