[1] |
COLLOBERT R,WESTON J,BOTTOU L,et al.Natural language processing(almost) from scratch[EB/OL].[2019-10-17].https://blog.csdn.net/tuqinag/article/details/43889795.
|
[2] |
LAMPLE G,BALLESTEROS M,SUBRAMANIAN S,et al.Neural architectures for named entity recognition[EB/OL].[2019-10-17].https://arxiv.org/abs/1603.01360.
|
[3] |
YANG Y S,ZHANG M S,CHEN W L,et al.Adversarial learning for Chinese NER from crowd annotations[EB/OL].[2019-10-17].https://arxiv.org/abs/1801.05147.
|
[4] |
ZHU Y Y,WANG G X,KARLSSON B.CAN-NER:convolutional attention network for Chinese named entity recognition[EB/OL].[2019-10-17].https://arxiv.org/abs/1904.02141.
|
[5] |
LU Yanan,ZHANG Yue,JI Donghong.Multi-prototype Chinese character embedding[C]//Proceedings of the 10th International Conference on Language Resources and Evaluation.Philadelphia,USA:ACL Press,2016:855-859.
|
[6] |
DONG Chuanhai,ZHANG Jiajun,ZONG Chengqing,et al.Character based LSTM-CRF with radical-level features for Chinese named entity recognition[C]//Proceedings of International Conference on Computer Processing of Oriental Languages.Berlin,Germany:Springer,2016:239-250.
|
[7] |
NADEAU D,SEKINE S.A survey of named entity recognition and classification[J].Lingvisticae Investiga-tiones,2007,30(1):3-26.
|
[8] |
SINGH T D,BANDYOPADHYAY S.Web based Manipuri corpus for multiword NER and Reduplicated MWEs identification using SVM[C]//Proceedings of International Conference on Computational Linguistics.Beijing:Chinese Information Society of China,2013:35-42.
|
[9] |
KONKOL M,KONOPÍK M.CRF-based Czech named entity recognizer and consolidation of Czech NER research[C]//Proceedings of International Conference on Text,Speech and Dialogue.Berlin,Germany:Springer,2013:153-160.
|
[10] |
SANTOS C D,GUIMARAES V,NITEROI R J,et al.Boosting named entity recognition with neural character embeddings[EB/OL].[2019-10-17].https://arxiv.org/abs/1505.05008.
|
[11] |
ZHANG Yingcheng,YANG Yang,JIANG Rui,et al.Commercial intelligence entity recognition model based on BiLSTM-CRF[J].Computer Engineering,2019,45(5):308-314. (in Chinese)张应成,杨洋,蒋瑞,等.基于BiLSTM-CRF的商情实体识别模型[J].计算机工程,2019,45(5):308-314.
|
[12] |
MA X Z,HOVY E.End-to-end sequence labeling via bi-directional LSTM-CNN-CRF[EB/OL].[2019-10-17].https://arxiv.org/abs/1603.01354.
|
[13] |
CHEN W L,ZHANG Y J,ISAHARA H.Chinese named entity recognition with conditional random fields[C]//Proceedings of the 5th SIGHAN Workshop on Chinese Language Processing.Washington D.C.,USA:IEEE Press,2006:118-121.
|
[14] |
HE Hangfeng,SUN Xu.F-score driven max margin neural network for named entity recognition in Chinese social media[EB/OL].[2019-10-17].https://arxiv.org/abs/1611.04234.
|
[15] |
HE Hangfeng,SUN Xu.A unified model for cross-domain and semi-supervised named entity recognition in Chinese social media[C]//Proceedings of AAAI'17.Palo Alto,USA:AAAI Press,2017:3216-3222.
|
[16] |
HUANG Zhiheng,XU Wei,YU Kai.Bidirectional LSTM-CRF models for sequence tagging[EB/OL].[2019-10-17].https://arxiv.org/abs/1508.01991.
|
[17] |
LIU L Y,SHANG J B,XU F,et al.Empower sequence labeling with task-aware neural language model[EB/OL].[2019-10-17].https://arxiv.org/abs/1709.04109.
|
[18] |
REI M.Semi-supervised multitask learning for sequence labeling[EB/OL].[2019-10-17].https://arxiv.org/abs/1704.07156.
|
[19] |
GE L,MOH T S.Improving text classification with word embedding[C]//Proceedings of IEEE International Conference on Big Data.Washington D.C.,USA:IEEE Press,2018:1-7.
|
[20] |
ANH L T,ARKHIPOV M Y,BURTSEV M S.Application of a hybrid Bi-LSTM-CRF model to the task of Russian named entity recognition[C]//Proceedings of Conference on Artificial Intelligence and Natural Language.Berlin,Germany:Springer,2017:91-103.
|
[21] |
JIANG X,HAVAEI M,CHARTRAND G,et al.On the importance of attention in meta-learning for few-shot text classification[EB/OL].[2019-10-17].https://arxiv.org/abs/1806.00852.
|
[22] |
BROCKNER J,HJELLE L,PLANT R W.Self-focused attention,self-esteem,and the experience of state depression[J].Journal of Personality,1985,53(3):425-434.
|
[23] |
ZHANG X,ZHAO J B,LECUN Y.Character-level convolutional networks for text classification[EB/OL].[2019-10-17].https://arxiv.org/abs/1509.01626.
|
[24] |
LI S,LI W Q,COOK C,et al.Independently Recurrent Neural Network(IndRNN):building a longer and deeper RNN[EB/OL].[2019-10-17].https://arxiv.org/abs/1803.04831.
|
[25] |
VASWANI A,SHAZEER N,PARMAR N,et al.Attention is all you need[C]//Proceedings of Proceedings of the 31st International Conference on Neural Information Processing Systems.New York,USA:ACM Press,2017:6000-6010.
|
[26] |
KIM Y.Convolutional neural networks for sentence classi-fication[C]//Proceedings of EMNLP'14.Washington D.C.,USA:IEEE Press,2014:1746-1751.
|
[27] |
LEE C,KIM Y B,LEE D,et al.Character-level feature extraction with densely connected networks[EB/OL].[2019-10-17].https://arxiv.org/abs/1806.09089.
|
[28] |
KRAL P.Features for named entity recognition in Czech language[C]//Proceedings of International Conference on Knowledge Discovery and Information Retrieval.Berlin,Germany:Springer,2011:1-8.
|