1 |
刘峤,李杨,段宏,等.知识图谱构建技术综述[J]. 计算机研究与发展,2016,53(3):582-600. 10.7544/issn1000-1239.2016.20148228
|
|
LIU Q, LI Y, DUAN H, et al. Knowledge graph construction techniques[J]. Journal of Computer Research and Development, 2016, 53(3): 582-600. 10.7544/issn1000-1239.2016.20148228
|
2 |
徐健,张智雄,吴振新.实体关系抽取的技术方法综述[J]. 现代图书情报技术,2008,24(8):18-23. 10.3969/j.issn.1003-3513.2008.08.004
|
|
XU J, ZHANG Z X, WU Z X. Review on techniques of entity relation extraction[J]. New Technology of Library and Information Service, 2008, 24(8): 18-23. 10.3969/j.issn.1003-3513.2008.08.004
|
3 |
CHEN Y P, WU Y F, QIN Y B, et al. Recognizing nested named entity based on the neural network boundary assembling model[J]. IEEE Intelligent Systems, 2020, 35(1): 74-81. 10.1109/mis.2019.2952334
|
4 |
CHEN Y P, WANG G R, ZHENG Q H, et al. A set space model to capture structural information of a sentence[J]. IEEE Access, 2019, 7:142515-142530. 10.1109/access.2019.2944559
|
5 |
CHEN Y P, WANG K, YANG W Z, et al. A multi-channel deep neural network for relation extraction[J]. IEEE Access, 2020, 8: 13195-13203. 10.1109/access.2020.2966303
|
6 |
WANG J, LU W. Two are better than one: joint entity and relation extraction with table-sequence encoders[C]// Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA: ACL, 2020: 1706-1721. 10.18653/v1/2020.emnlp-main.133
|
7 |
鄂海红,张文静,肖思琪,等. 深度学习实体关系抽取研究综述[J]. 软件学报, 2019, 30(6):1793-1818. 10.13328/j.cnki.jos.005817
|
|
E H H, ZHANG W J, XIAO S Q, et al. Survey of entity relationship extraction based on deep learning[J]. Journal of Software, 2019, 30(6):1793-1818. 10.13328/j.cnki.jos.005817
|
8 |
HASHIMOTO K, MIWA M, TSURUOKA Y, et al. Simple customization of recursive neural networks for semantic relation classification[C]// Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA: ACL, 2013: 1372-1376. 10.3115/v1/d14-1163
|
9 |
ZENG D J, LIU K, LAI S W, et al. Relation classification via convolutional deep neural network[C]// Proceedings of the 25th International Conference on Computational Linguistics: Technical Papers. Stroudsburg, PA: ACL, 2014: 2335-2344.
|
10 |
WANG L L, CAO Z, DE MELO G, et al. Relation classification via multi-level attention CNNs[C]// Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA: ACL, 2016: 1298-1307. 10.18653/v1/p16-1123
|
11 |
LI F, ZHANG M S, FU G H, et al. A Bi-LSTM-RNN model for relation classification using low-cost sequence features[EB/OL]. [2021-10-28].. 10.7753/ijsea1009.1006
|
12 |
MIWA M, BANSAL M. End-to-end relation extraction using LSTMs on sequences and tree structures[C]// Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA: ACL, 2016: 1105-1116. 10.18653/v1/p16-1105
|
13 |
LI F, ZHANG M S, FU G H, et al. A neural joint model for extracting bacteria and their locations[C]// Proceedings of the 2017 Pacific-Asia Conference on Knowledge Discovery and Data Mining, LNCS 10235/LNAI 10235. Cham: Springer, 2017: 15-26.
|
14 |
KATIYAR A, CARDIE C. Investigating LSTMs for joint extraction of opinion entities and relations[C]// Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA: ACL, 2016: 919-929. 10.18653/v1/p16-1087
|
15 |
KATIYAR A, CARDIE C. Going out on a limb: joint extraction of entity mentions and relations without dependency trees[C]// Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA: ACL, 2017: 917-928. 10.18653/v1/p17-1085
|
16 |
ZHENG S C, WANG F, BAO H Y, et al. Joint extraction of entities and relations based on a novel tagging scheme[C]// Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA: ACL, 2017: 1227-1236. 10.18653/v1/p17-1113
|
17 |
LI Q, JI H. Incremental joint extraction of entity mentions and relations[C]// Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Stroudsburg, PA: Association for Computational Linguistics, 2014: 402-412. 10.3115/v1/p14-1038
|
18 |
ZHANG M S, ZHANG Y, FU G H. End-to-end neural relation extraction with global optimization[C]// Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, PA: ACL, 2017: 1730-1740. 10.18653/v1/d17-1182
|
19 |
LI X Y, YIN F, SUN Z J, et al. Entity-relation extraction as multi-turn question answering[C]// Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA: ACL, 2019: 1340-1350. 10.18653/v1/p19-1129
|