A comparative study of Chinese named entity recognition with different segment representations
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A comparative study of Chinese named entity recognition with different segment representations
Authors
Keywords
-
Journal
APPLIED INTELLIGENCE
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2022-02-06
DOI
10.1007/s10489-022-03274-0
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- A Novel Attribute-Based Encryption Approach with Integrity Verification for CAD Assembly Models
- (2021) Yueting Yang et al. Engineering
- A hybrid deep-learning approach for complex biochemical named entity recognition
- (2021) Jian Liu et al. KNOWLEDGE-BASED SYSTEMS
- Fundamentals of Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) network
- (2020) Alex Sherstinsky PHYSICA D-NONLINEAR PHENOMENA
- A full migration BBO algorithm with enhanced population quality bounds for multimodal biomedical image registration
- (2020) Yilin Chen et al. APPLIED SOFT COMPUTING
- Leveraging maximum entropy and correlation on latent factors for learning representations
- (2020) Zhicheng He et al. NEURAL NETWORKS
- Enhanced sequence labeling based on latent variable conditional random fields
- (2020) Jerry Chun-Wei Lin et al. NEUROCOMPUTING
- 3D mesh simplification with feature preservation based on Whale Optimization Algorithm and Differential Evolution
- (2020) Yaqian Liang et al. INTEGRATED COMPUTER-AIDED ENGINEERING
- Crosslingual named entity recognition for clinical de-identification applied to a COVID-19 Italian data set
- (2020) Rosario Catelli et al. APPLIED SOFT COMPUTING
- ASRNN: A recurrent neural network with an attention model for sequence labeling
- (2020) Jerry Chun-Wei Lin et al. KNOWLEDGE-BASED SYSTEMS
- The impact of using different annotation schemes on named entity recognition
- (2020) Nasser Alshammari et al. Egyptian Informatics Journal
- A Survey on Deep Learning for Named Entity Recognition
- (2020) Jing Li et al. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
- Differential convolutional neural network
- (2019) M. Sarıgül et al. NEURAL NETWORKS
- DRCDN: learning deep residual convolutional dehazing networks
- (2019) Shengdong Zhang et al. VISUAL COMPUTER
- Core techniques of question answering systems over knowledge bases: a survey
- (2017) Dennis Diefenbach et al. KNOWLEDGE AND INFORMATION SYSTEMS
- Enhancing medical named entity recognition with an extended segment representation technique
- (2015) Sara Keretna et al. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Deep learning
- (2015) Yann LeCun et al. NATURE
- A comparison of conditional random fields and structured support vector machines for chemical entity recognition in biomedical literature
- (2015) Buzhou Tang et al. Journal of Cheminformatics
- Named entity recognition with multiple segment representations
- (2013) Han-Cheol Cho et al. INFORMATION PROCESSING & MANAGEMENT
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreDiscover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversation