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Chinese Named Entity Recognition
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Chinese named entity recognition is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc. from Chinese text (Source: Adapted from Wikipedia).
논문
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Student-Powered Digital Scholarship CoLab Project in the HKUST Library: Develop a Chinese Named-Entity Recognition (NER) Tool within One Semester from the Ground Up
HREB-CRF: Hierarchical Reduced-bias EMA for Chinese Named Entity Recognition
CRENER: A Character Relation Enhanced Chinese NER Model
Unified Lattice Graph Fusion for Chinese Named Entity Recognition
Supplementary Features of BiLSTM for Enhanced Sequence Labeling
DiffusionNER: Boundary Diffusion for Named Entity Recognition
Unsupervised Boundary-Aware Language Model Pretraining for Chinese Sequence Labeling
Improving Chinese Named Entity Recognition by Search Engine Augmentation
Application of Data Encryption in Chinese Named Entity Recognition
Rethinking the Value of Gazetteer in Chinese Named Entity Recognition
NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
Boundary Smoothing for Named Entity Recognition
Delving Deep into Regularity: A Simple but Effective Method for Chinese Named Entity Recognition
Using Domain Knowledge for Low Resource Named Entity Recognition
Parallel Instance Query Network for Named Entity Recognition
MarkBERT: Marking Word Boundaries Improves Chinese BERT
Unified Named Entity Recognition as Word-Word Relation Classification
A New Multifractal-based Deep Learning Model for Text Mining
MFE-NER: Multi-feature Fusion Embedding for Chinese Named Entity Recognition
MECT: Multi-Metadata Embedding based Cross-Transformer for Chinese Named Entity Recognition
Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
A More Efficient Chinese Named Entity Recognition base on BERT and Syntactic Analysis
Named Entity Recognition for Social Media Texts with Semantic Augmentation
Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
FLAT: Chinese NER Using Flat-Lattice Transformer
Incorporating Uncertain Segmentation Information into Chinese NER for Social Media Text
FGN: Fusion Glyph Network for Chinese Named Entity Recognition
CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
Chinese Named Entity Recognition Augmented with Lexicon Memory
TENER: Adapting Transformer Encoder for Named Entity Recognition
Porous Lattice-based Transformer Encoder for Chinese NER
Dice Loss for Data-imbalanced NLP Tasks
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
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