482 工程科学学报,第42卷,第4期 recognition based on cascading hidden Markov model.J Commun, [17]Chen Q Y,Cheng G,Li D,et al.Named entity recognition for 2006,27(2):87 mechanical design and manufacturing area.Comput Eng Appl, (俞鸿魁,张华平,刘群,等.基于层叠隐马尔可夫模型的中文命 2017,53(20):100 名实体识别.通信学报,2006,27(2):87) (陈秋瑗,程光,李迪,等.机械设计领域的命名实体识别研究 [8] He Y X,Luo C W.Hu B Y.Geographic entity recognition method 计算机工程与应用.2017,53(20):100) based on CRF model and rules combination.Comput Appl Sofiw, [18]Zhao X N,Feng Z P.Fault diagnosis of rolling element bearing 2015,32(1):179 based on ensemble empirical mode decomposition and cross (何炎样,罗楚威,胡彬尧.基于CRF和规则相结合的地理命名实 energy operator..Chin J Eng,2015,37(S1):片65 体识别方法.计算机应用与软件,2015,32(1):179) (赵晓宁,冯志鹏.基于集合经验模式分解和交叉能量算子的滚 [9] Wang LL,Aishan W,Maihemuti M,et al.A semi-supervised 动轴承故障诊断.工程科学学报,2015,37(S1):65) approach to Uyghur named entity recognition based on CRF.J [19]Zhang D,Feng Z P.Fault diagnosis of rolling bearings based on Chin Inf Process,2018,32(11):16 variational mode decomposition and calculus enhanced energy (王路路,艾山吾买尔,买合木提·买买提,等,基于CRF和半监 operator.Chin J Eng,2016,38(9):1327 督学习的维吾尔文命名实体识别.中文信息学报,2018, (张东,冯志鹏.基于变分模式分解和微积分增强能量算子的滚 32(11):16) 动轴承故障诊断.工程科学学报,2016,38(9):1327) [10]Hochreiter S,Schmidhuber J.Long short-term memory.Neural [20]Zhao W H,Zhang X.Lv D,et al.Technical status and strategies Comput,1997,9(8):1735 for domestic CNC machine tools.Aeron Manyf Technol,2016, [11]Graves A,Schmidhuber J.Framewise phoneme classification with 59(9):16 bidirectional LSTM and other neural network architectures.Neural (赵万华,张星,吕盾,等.国产数控机床的技术现状与对策.航 Nenm,2005,18(5-6):602 空制造技术,2016,59(9):16) [12]Yang H M,Li L,Yang R D,et al.Named entity recognition based [21]Mikolov T,Sutskever I,Chen K,et al.Distributed representations on bidirectional long short-term memory combined with case of words and phrases and their compositionality /Advances in report form.ChinJ Tissue Eng Res,2018,22(20):3237 Neural Information Processing Systems 26(NIPS 2013).Lake (杨红梅,李琳,杨日东,等.基于双向LSTM神经网路电子病历 Tahoe,2013:3111 命名实体的识别模型.中国组织工程研究,2018,22(20):3237) [13]Lin B Y,Xu F,Luo Z Y,et al.Multi-channel BiLSTM-CRF model [22]Lafferty J,McCallum A,Pereira F C N.Conditional random fields: Probabilistic models for segmenting and labeling sequence data / for emerging named entity recognition in social media / Proceedings of the 3rd Workshop on Noisy User-generated Text. Proceedings of the 18th International Conference on Machine Copenhagen,2017:160 Learning 2001.Williamstown,2001:282 [14]Bharadwaj A,Mortensen D,Dyer C,et al.Phonologically aware [23]Yuan S,Tang J,Gu X T.A summary of scholars'portrait neural model for named entity recognition in low resource transfer techniques in the open interet.Comput Res Dev,2018,55(9): settings I/Proceedings of the 2016 Conference on Empirical 1903 Methods in Natural Language Processing.Austin,2016:1462 (袁莎,唐杰,顾晓韬.开放互联网中的学者画像技术综述.计算 [15]Li C Y,Wu Y Z,Hu F H,et al.Packaging domain-based named 机研究与发展,2018,55(9):1903) entity recognition with multi-layer neural networks.Neu- [24]Zhu W Q,Liu Q.Conditional random fields with loop and its oQuantology,2018,16(6):564 inference algorithm.Compur Eng Appl,008,44(28):180 [16]Yi S X,Yin H P,Zheng H Y.Public security event trigger (朱文球,刘强.基于条件随机域的上下文人类动作识别.计算 identification based on Bidirectional LSTM.Chin J Eng,2019, 机工程与应用,2008,44(28):180) 41(9):1201 [25]Lai S W.Word and document embeddings based on neural (易士翔,尹宏鹏,郑恒毅.基于BiLSTM的公共安全事件触发词 network approaches[J/OL]arXiv preprint (2016-11-18)2019-09- 识别.工程科学学报,2019,41(9):1201) 17].https://arxiv.org/abs/1611.05962recognition based on cascading hidden Markov model. J Commun, 2006, 27(2): 87 (俞鸿魁, 张华平, 刘群, 等. 基于层叠隐马尔可夫模型的中文命 名实体识别. 通信学报, 2006, 27(2):87) He Y X, Luo C W, Hu B Y. Geographic entity recognition method based on CRF model and rules combination. Comput Appl Softw, 2015, 32(1): 179 (何炎祥, 罗楚威, 胡彬尧. 基于CRF和规则相结合的地理命名实 体识别方法. 计算机应用与软件, 2015, 32(1):179) [8] Wang L L, Aishan W, Maihemuti M, et al. A semi-supervised approach to Uyghur named entity recognition based on CRF. J Chin Inf Process, 2018, 32(11): 16 (王路路, 艾山•吾买尔, 买合木提•买买提, 等. 基于CRF和半监 督 学 习 的 维 吾 尔 文 命 名 实 体 识 别 . 中 文 信 息 学 报 , 2018, 32(11):16) [9] Hochreiter S, Schmidhuber J. Long short-term memory. Neural Comput, 1997, 9(8): 1735 [10] Graves A, Schmidhuber J. Framewise phoneme classification with bidirectional LSTM and other neural network architectures. Neural Netw, 2005, 18(5-6): 602 [11] Yang H M, Li L, Yang R D, et al. Named entity recognition based on bidirectional long short-term memory combined with case report form. Chin J Tissue Eng Res, 2018, 22(20): 3237 (杨红梅, 李琳, 杨日东, 等. 基于双向LSTM神经网络电子病历 命名实体的识别模型. 中国组织工程研究, 2018, 22(20):3237) [12] Lin B Y, Xu F, Luo Z Y, et al. Multi-channel BiLSTM-CRF model for emerging named entity recognition in social media // Proceedings of the 3rd Workshop on Noisy User-generated Text. Copenhagen, 2017: 160 [13] Bharadwaj A, Mortensen D, Dyer C, et al. Phonologically aware neural model for named entity recognition in low resource transfer settings // Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. Austin, 2016: 1462 [14] Li C Y, Wu Y Z, Hu F H, et al. Packaging domain-based named entity recognition with multi-layer neural networks. NeuroQuantology, 2018, 16(6): 564 [15] Yi S X, Yin H P, Zheng H Y. Public security event trigger identification based on Bidirectional LSTM. Chin J Eng, 2019, 41(9): 1201 (易士翔, 尹宏鹏, 郑恒毅. 基于BiLSTM的公共安全事件触发词 识别. 工程科学学报, 2019, 41(9):1201) [16] Chen Q Y, Cheng G, Li D, et al. Named entity recognition for mechanical design and manufacturing area. Comput Eng Appl, 2017, 53(20): 100 (陈秋瑗, 程光, 李迪, 等. 机械设计领域的命名实体识别研究. 计算机工程与应用, 2017, 53(20):100) [17] Zhao X N, Feng Z P. Fault diagnosis of rolling element bearing based on ensemble empirical mode decomposition and cross energy operator. Chin J Eng, 2015, 37(S1): 65 (赵晓宁, 冯志鹏. 基于集合经验模式分解和交叉能量算子的滚 动轴承故障诊断. 工程科学学报, 2015, 37(S1):65) [18] Zhang D, Feng Z P. Fault diagnosis of rolling bearings based on variational mode decomposition and calculus enhanced energy operator. Chin J Eng, 2016, 38(9): 1327 (张东, 冯志鹏. 基于变分模式分解和微积分增强能量算子的滚 动轴承故障诊断. 工程科学学报, 2016, 38(9):1327) [19] Zhao W H, Zhang X, Lv D, et al. Technical status and strategies for domestic CNC machine tools. Aeron Manuf Technol, 2016, 59(9): 16 (赵万华, 张星, 吕盾, 等. 国产数控机床的技术现状与对策. 航 空制造技术, 2016, 59(9):16) [20] Mikolov T, Sutskever I, Chen K, et al. Distributed representations of words and phrases and their compositionality // Advances in Neural Information Processing Systems 26(NIPS 2013). Lake Tahoe, 2013: 3111 [21] Lafferty J, McCallum A, Pereira F C N. Conditional random fields: Probabilistic models for segmenting and labeling sequence data // Proceedings of the 18th International Conference on Machine Learning 2001. Williamstown, 2001: 282 [22] Yuan S, Tang J, Gu X T. A summary of scholars' portrait techniques in the open internet. J Comput Res Dev, 2018, 55(9): 1903 (袁莎, 唐杰, 顾晓韬. 开放互联网中的学者画像技术综述. 计算 机研究与发展, 2018, 55(9):1903) [23] Zhu W Q, Liu Q. Conditional random fields with loop and its inference algorithm. Comput Eng Appl, 2008, 44(28): 180 (朱文球, 刘强. 基于条件随机域的上下文人类动作识别. 计算 机工程与应用, 2008, 44(28):180) [24] Lai S W. Word and document embeddings based on neural network approaches[J/OL]. arXiv preprint (2016-11-18)[2019-09- 17]. https://arxiv.org/abs/1611.05962 [25] · 482 · 工程科学学报,第 42 卷,第 4 期