Results 31 to 40 of about 1,332,615 (213)

A lattice-transformer-graph deep learning model for Chinese named entity recognition

Journal of Intelligent Systems, 2023
Named entity recognition (NER) is the localization and classification of entities with specific meanings in text data, usually used for applications such as relation extraction, question answering, etc.
Lin Min, Xu Yanyan, Cai Chenghao, Ke Dengfeng, Su Kaile   +4 more
doaj   +1 more source

Dual Neural Network Fusion Model for Chinese Named Entity Recognition

International Journal of Computational Intelligence Systems, 2020
Chinese named entity recognition (NER) has important effect on natural language processing (NLP) applications. This recognition task is complicated in its strong dependent-relation, missing delimiters in the text and insufficient feature representation ...
Dandan Zhao, Jingxiang Cao, Degen Huang, Jiana Meng, Pan Zhang   +4 more
doaj   +1 more source

Simplify the Usage of Lexicon in Chinese NER

CoRR, 2019
ACL ...
Minlong Peng, Ruotian Ma, Qi Zhang 0001, Xuanjing Huang 0001   +3 more
openaire   +2 more sources

Entity Enhanced BERT Pre-training for Chinese NER [PDF]

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
Character-level BERT pre-trained in Chinese suffers a limitation of lacking lexicon information, which shows effectiveness for Chinese NER. To integrate the lexicon into pre-trained LMs for Chinese NER, we investigate a semi-supervised entity enhanced BERT pre-training method. In particular, we first extract an entity lexicon from the relevant raw text
Chen Jia, Yuefeng Shi, Qinrong Yang, Yue Zhang   +3 more
openaire   +1 more source

A Lexicon-Based Graph Neural Network for Chinese NER [PDF]

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019
Recurrent neural networks (RNN) used for Chinese named entity recognition (NER) that sequentially track character and word information have achieved great success. However, the characteristic of chain structure and the lack of global semantics determine that RNN-based models are vulnerable to word ambiguities.
Tao Gui, Yicheng Zou, Qi Zhang 0001, Minlong Peng, Jinlan Fu, Zhongyu Wei, Xuanjing Huang 0001   +6 more
openaire   +1 more source

MTLAT: A Multi-Task Learning Framework Based on Adversarial Training for Chinese Cybersecurity NER

, 2020
Part 2: AIInternational audienceWith the continuous development of cybersecurity texts, the importance of Chinese cybersecurity named entity recognition (NER) is increasing.
Jiang, Zhengwei, Yaopeng Han, Li, Ning, Zhigang Lu, Yuling Liu, Bo Jiang, Zhengwei Jiang, Jiang, Bo, Zhang, Chen, Lu, Zhigang, Chen Zhang, Liu, Yuling, Ning Li, Han, Yaopeng   +13 more
core   +1 more source

MoGCN: Mixture of Gated Convolutional Neural Network for Named Entity Recognition of Chinese Historical Texts

IEEE Access, 2020
Named Entity Recognition (NER) systems have been largely advanced by deep neural networks in the recent decade. However, the state-of-the-arts on NER have been less applied to Chinese historical texts due to the lack of standard corpora in Chinese ...
Chengxi Yan, Qi Su, Jun Wang
doaj   +1 more source

Chinese NER with Height-Limited Constituent Parsing

Proceedings of the AAAI Conference on Artificial Intelligence, 2019
In this paper, we investigate how to improve Chinese named entity recognition (NER) by jointly modeling NER and constituent parsing, in the framework of neural conditional random fields (CRF). We reformulate the parsing task to heightlimited constituent parsing, by which the computational complexity can be significantly reduced, and the majority of ...
Rui Wang, Xin Xin 0001, Wei Chang, Kun Ming, Biao Li, Xin Fan   +5 more
openaire   +3 more sources

A Neural Multi-digraph Model for Chinese NER with Gazetteers [PDF]

Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019
Gazetteers were shown to be useful resources for named entity recognition (NER). Many existing approaches to incorporating gazetteers into machine learning based NER systems rely on manually defined selection strategies or handcrafted templates, which may not always lead to optimal effectiveness, especially when multiple gazetteers are involved.
Ruixue Ding, Pengjun Xie, Xiaoyan Zhang, Wei Lu 0011, Linlin Li 0001, Luo Si   +5 more
openaire   +2 more sources

Photoactivated Platinum Complexes: Targeting Membrane Proteins and Organelles for Precision Cancer Therapy

Angewandte Chemie, EarlyView.
This review highlights an emerging anticancer approach integrating platinum agents into photodynamic therapy (PDT) and photoactivated chemotherapy (PACT) systems, further augmented by cancer cell membrane‐ and organelle‐targeting. By directing photoactivated platinum complexes from nontargeted distribution to cancer cells or defined subcellular sites ...
Shu Chen, Qiyuan Zhou, Jiaqian Xu, Guangyu Zhu   +3 more
wiley   +2 more sources