This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Wang Ning, GE Ruifang, Yuan Chunfa, Huang Jinhui, LI Wenjie. Recognition of company names in Chinese Financial News., 2002(02):1–6.WangNingGERuifangYuanChunfaHuangJinhuiLIWenjie. ., 2002(02):1–6.Search in Google Scholar
Wang S, Xu R, Liu B, et al. Financial named entity recognition based on conditional random fields and information entropy[C]//2014 International Conference on Machine Learning and Cybernetics. Lanzhou: IEEE, 2014: 838-843.WangSXuRLiuB,Financial named entity recognition based on conditional random fields and information entropy[C]//. Lanzhou: IEEE, 2014: 838–843.Search in Google Scholar
Qian-yu li. Financial entity oriented knowledge map construction research [D]. Yunnan university of finance and economics, 2020, DOI: 10.27455 /, dc nki. Gycmc. 2020.000492.Qian-yuliFinancial entity oriented knowledge map construction research [D]. , 2020, DOI: 10.27455/,dcnki.Gycmc.2020.000492.Open DOISearch in Google Scholar
Wang Guoming. Based on the deep study of the financial sector knowledge map construction research [D]. The northeast normal university, 2021. The DOI: 10.27011 /, dc nki. Gdbsu. 2021.000237.WangGuomingBased on the deep study of the financial sector knowledge map construction research [D]. , 2021. The DOI: 10.27011/,dcnki.Gdbsu.2021.000237.Open DOISearch in Google Scholar
He Yunqi, Liu Suwen, Qian Longhua, et al. Disease Name Recognition Based on Syntactic and Semantic features [J]. Science China Information Science, 2018, 48 (11): 1546-1557.HeYunqiLiuSuwenQianLonghuaDisease Name Recognition Based on Syntactic and Semantic features [J]. , 2018, 48 (11): 1546–1557.Search in Google Scholar
Yu L, Lu F, Liu X. A bootstrapping based approach for open geo-entity relation extraction [J].Acta Geodaetica et Cartographica Sinica, 2016, 45(5): 616-622.YuLLuFLiuX.A bootstrapping based approach for open geo-entity relation extraction [J]., 2016, 45(5): 616–622.Search in Google Scholar
Kambhatla N. Combining lexical, syntactic, and semantic features with maximum entropy models for information extraction[C]//Proceedings of the ACL Interactive Poster and Demonstration Sessions. 2004: 178-181.KambhatlaN.Combining lexical, syntactic, and semantic features with maximum entropy models for information extraction[C]//. 2004: 178–181.Search in Google Scholar
Liu J, Ren H, Wu M, et al. Multiple relations extraction among multiple entities in unstructured text [J]. Soft Computing, 2018, 22(13): 4295-4305.LiuJRenHWuMMultiple relations extraction among multiple entities in unstructured text [J]. , 2018, 22(13): 4295–4305.Search in Google Scholar
Zhao Pengwu, Li Zhiyi, Lin Xiaoqi. Chinese Character Relation Extraction and Recognition Based on Attention Mechanism and Convolutional Neural Network [J/OL]. Data analysis and knowledge discovery: 1-16 [2022-05-26]. http://kns.cnki.net/kcms/detail/10.1478.G2.20220511.1654.008.htmlZhaoPengwuLiZhiyiLinXiaoqiChinese Character Relation Extraction and Recognition Based on Attention Mechanism and Convolutional Neural Network [J/OL]. : 1–16 [2022-05-26]. HTTP://http://kns.cnki.net/kcms/detail/10.1478.G2.20220511.1654.008.htmlSearch in Google Scholar