Journal of Shandong University(Engineering Science) ›› 2023, Vol. 53 ›› Issue (6): 16-25.doi: 10.6040/j.issn.1672-3961.0.2023.127
• Machine Learning & Data Mining • Previous Articles
ZHENG Jingfei, LIAO Yongxin, WANG Huazhen, HE Ting*
CLC Number:
[1] 冯钧, 魏大保, 苏栋, 等. 文档级实体关系抽取方法研究综述[J]. 计算机科学, 2022, 49(10): 224-242. FENG Jun, WEI Dabao, SU Dong, et al. Survey of document-level entity relation extraction methods[J]. Computer Science, 2022, 49(10): 224-242. [2] YAO Y, YE D, LI P, et al. DocRED: a large-scale document-level relation extraction dataset[C] //Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Florence, Italy: ACL, 2019: 764-777. [3] VERGA P, STRUBELL E, MCCALLUM A. Simultaneously self-attending to all mentions for full-abstract biological relation extraction[C] //Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. New Orleans, USA: ACL, 2018: 872-884. [4] MIKOLOV T, SUTSKEVER I, CHEN K, et al. Distributed representations of words and phrases and their compositionality[C] //Proceedings of the 26th International Conference on Neural Information Processing Systems. Nevada, USA: MIT Press, 2013:3111-3119. [5] PENNINGTON J, SOCHER R, MANNING C D. Glove: global vectors for word representation[C] /Proceedings of the 2014 conference on empirical methods in natural Ianguage processing. Stroudsburg, USA: ACL, 2014: 1532-1543. [6] DEVLIN J, CHANG M W, LEE K, et al. BERT: pre-training of deep bidirectional transformers for language understanding[C] //Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Minneapolis, USA: ACL, 2019: 4171-4186. [7] KIPF T N, WELLING M. Semi-supervised classification with graph convolutional networks[C] //The 5th International Conference on Learning Representations. Toulon, France: ICLR, 2017: 1-14. [8] VELICKOVIC P, CUCURULL G, CASANOVA A, et al. Graph attention networks[C] //The 6th International Conference on Learning Representations. Vancouver, Canada: ICLR, 2018: 1-12. [9] GUO Z, ZHANG Y, LU W. Attention guided graph convolutional networks for relation extraction[C] //Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Florence, Italy: ACL, 2019: 241-251. [10] SAHU S, CHRISTOPOULOU E, MIWA M, et al. Inter-sentence relation extraction with document-level graph convolutional neural network[C] // Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Florence, Italy: ACL, 2019: 4309-4316. [11] NAN G, GUO Z, SEKULIC I, et al. Reasoning with latent structure refinement for document-level relation extraction[C] //Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics. Seattle, USA: ACL, 2020: 1546-1557. [12] ZENG S, XU R, CHANG B, et al. Double graph based reasoning for document-level relation extraction[C] //Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing. Punta Cana, Dominican: ACL, 2020: 1630-1640. [13] PENG X, ZHANG C, XU K. Document-level relation extraction via subgraph reasoning[C] //Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. Messe Wien, Austria: Morgan Kaufmann, 2022: 4331-4337. [14] PARK S, YOON D, KIM H. Improving graph-based document-Level relation extraction model with novel graph structure[C] //Proceedings of the 31st ACM International Conference on Information & Knowledge Management. Atlanta, USA: ACM, 2022: 4379-4383. [15] XU W, CHEN K, ZHAO T. Discriminative reasoning for document-level relation extraction[C] //Findings of the Association for Computational Linguistics. Bangkok, Thailand: ACL, 2021: 1653-1663. [16] XU W, CHEN K, MOU L, et al. Document-level relation extraction with sentences importance estimation and focusing[C] //Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Seattle, USA: ACL, 2022: 2920-2929. [17] YU J, YANG D, TIAN S. Relation-specific attentions over entity mentions for enhanced document-Level relation extraction[C] //Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Seattle, USA: ACL, 2022: 1523-1529. [18] CHRISTOPOULOU F, MIWA M, ANANIADOU S. Connecting the dots: document-level neural relation extraction with edge-oriented graphs[C] //Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing. HongKong, China: ACL, 2019: 4925-4936. [19] VASWANI A, SHAZEER N, PARMAR N, et al. Attention is all you need [C] //Proceedings of the 31st International Conference on Neural Information Processing Systems. Long Beach, USA: MIT Press, 2017: 1-11. [20] VRANDECIC D, KRÖTZSCH M. Wikidata: a free collaborative knowledgebase[J]. Communications of the ACM, 2014, 57(10): 78-85. [21] LI J, SUN Y, JOHNSON R J, et al. BioCreative V CDR task corpus: a resource for chemical disease relation extraction[EB/OL].(2016-05-08)[2023-06-12]. https://pubmed.ncbi.nlm.nih.gov/27161011/ [22] WU Y, LUO R, LEUNG H C M, et al. Renet: a deep learning approach for extracting gene-disease associations from literature[C] //Research in Computational Molecular Biology: 23rd Annual International Conference. Washington, USA: Springer International Publishing, 2019: 272-284. [23] PIÑERO J, BRAVO À, QUERALT-ROSINACH N, et al. DisGeNET: a comprehensive platform integrating information on human disease-associated genes and variants[J]. Nucleic Acids Research, 2017, 45(1): 833-839. [24] TANG H, CAO Y, ZHANG Z, et al. Hin: hierarchical inference network for document-level relation extraction[C] //Pacific Asia Conference on Knowledge Discovery and Data Mining. Singapore: Springer, 2020: 197-209. [25] ZENG S, WU Y, CHANG B. SIRE: Separate intra-and inter-sentential reasoning for document-level relation extraction[C] // Findings of the Association for Computational Linguistics. Bangkok, Thailand: ACL, 2021: 524-534. [26] HUANG Q, ZHU S, FENG Y, et al. Three sentences are all you need: local path enhanced document relation extraction[C] // Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing. Bangkok, Thailand: ACL, 2021: 998-1004. [27] LEE J, YOON W, KIM S, et al. BioBERT: a pre-trained biomedical language representation model for biomedical text mining[J]. Bioinformatics, 2020, 36(4): 1234-1240. |
[1] | Yujiang FAN,Huanhuan HUANG,Jiaxiong DING,Kai LIAO,Binshan YU. Resilience evaluation system of the old community based on cloud model [J]. Journal of Shandong University(Engineering Science), 2023, 53(5): 1-9, 19. |
[2] | Ying LI,Jiankun WANG. The classification of mild cognitive impairment based on supervised graph regularization and information fusion [J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 65-73. |
[3] | LIU Xing, YANG Lu, HAO Fanchang. Finger vein image retrieval based on multi-feature fusion [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 118-126. |
[4] | YU Yixuan, YANG Geng, GENG Hua. Multimodal hierarchical keyframe extraction method for continuous combined motion [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 42-50. |
[5] | ZHANG Hao, LI Ziling, LIU Tong, ZHANG Dawei, TAO Jianhua. A technology prediction model based on fuzzy Bayesian networks with sociological factors [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 23-33. |
[6] | WU Yanli, LIU Shuwei, HE Dongxiao, WANG Xiaobao, JIN Di. Poisson-gamma topic model of describing multiple underlying relationships [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 51-60. |
[7] | YU Mingjun, DIAO Hongjun, LING Xinghong. Online multi-object tracking method based on trajectory mask [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 61-69. |
[8] | HUANG Huajuan, CHENG Qian, WEI Xiuxi, YU Chuchu. Adaptive crow search algorithm with Jaya algorithm and Gaussian mutation [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 11-22. |
[9] | LIU Fangxu, WANG Jian, WEI Benzheng. Auxiliary diagnosis algorithm for pediatric pneumonia based on multi-spatial attention [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 135-142. |
[10] | Yue YUAN,Yanli WANG,Kan LIU. Named entity recognition model based on dilated convolutional block architecture [J]. Journal of Shandong University(Engineering Science), 2022, 52(6): 105-114. |
[11] | Xiaobin XU,Qi WANG,Bin GAO,Zhiyu SUN,Zhongjun LIANG,Shangguang WANG. Pre-allocation of resources based on trajectory prediction in heterogeneous networks [J]. Journal of Shandong University(Engineering Science), 2022, 52(4): 12-19. |
[12] | Yinfeng MENG,Qingfang LI. Recognition learning based on multivariate functional principal component representation [J]. Journal of Shandong University(Engineering Science), 2022, 52(3): 1-8. |
[13] | Xiushan NIE,Yuling MA,Huiyan QIAO,Jie GUO,Chaoran CUI,Zhiyun YU,Xingbo LIU,Yilong YIN. Survey on student academic performance prediction from the perspective of task granularity [J]. Journal of Shandong University(Engineering Science), 2022, 52(2): 1-14. |
[14] | Tongyu JIANG, Fan CHEN, Hongjie HE. Lightweight face super-resolution network based on asymmetric U-pyramid reconstruction [J]. Journal of Shandong University(Engineering Science), 2022, 52(1): 1-8. |
[15] | Jun HU,Dongmei YANG,Li LIU,Fujin ZHONG. Cross social network user alignment via fusing node state information [J]. Journal of Shandong University(Engineering Science), 2021, 51(6): 49-58. |
|