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Chinese Word Segmentation

Chinese word segmentation is the task of splitting Chinese text (i.e. a sequence of Chinese characters) into words (Source: www.nlpprogress.com).

Papers

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Showing 51–100 of 244 papers

TitleStatusHype
Binary Tree based Chinese Word Segmentation—0
Can MDL Improve Unsupervised Chinese Word Segmentation?—0
Can Word Segmentation be Considered Harmful for Statistical Machine Translation Tasks between Japanese and Chinese?—0
Cascaded Chinese Weibo Segmentation Based on CRFs—0
Character-Level Chinese Dependency Parsing—0
An Empirical Study of Automatic Chinese Word Segmentation for Spoken Language Understanding and Named Entity Recognition—0
Chinese Grammatical Error Diagnosis Based on Policy Gradient LSTM Model—0
Chinese Morphological Analysis with Character-level POS Tagging—0
Chinese Spelling Check System Based on N-gram Model—0
Chinese-to-Japanese Patent Machine Translation based on Syntactic Pre-ordering forWAT 2015—0
Chinese-to-Japanese Patent Machine Translation based on Syntactic Pre-ordering for WAT 2016—0
Chinese Tweets Segmentation based on Morphemes—0
A Common Case of Jekyll and Hyde: The Synergistic Effect of Using Divided Source Training Data for Feature Augmentation—0
A realistic and robust model for Chinese word segmentation—0
A Joint Model for Graph-based Chinese Dependency Parsing—0
A Cascaded Approach for CIPS-SIGHAN Micro-Blog Word Segmentation Bakeoff 2012—0
Neural Chinese Word Segmentation with Lexicon and Unlabeled Data via Posterior Regularization—0
Context-Aware Word Segmentation for Chinese Real-World Discourse—0
Consistent Word Segmentation, Part-of-Speech Tagging and Dependency Labelling Annotation for Chinese Language—0
Approaching Neural Chinese Word Segmentation as a Low-Resource Machine Translation Task—0
Context-Based Chinese Word Segmentation using SVM Machine-Learning Algorithm without Dictionary Support—0
A Pragmatic Approach for Classical Chinese Word Segmentation—0
Co-regularizing character-based and word-based models for semi-supervised Chinese word segmentation—0
Coupled Sequence Labeling on Heterogeneous Annotations: POS Tagging as a Case Study—0
Comparison of the Impact of Word Segmentation on Name Tagging for Chinese and Japanese—0
Create a Manual Chinese Word Segmentation Dataset Using Crowdsourcing Method—0
CRFs-Based Chinese Word Segmentation for Micro-Blog with Small-Scale Data—0
DAG-based Long Short-Term Memory for Neural Word Segmentation—0
Deep Learning for Chinese Word Segmentation and POS Tagging—0
Deep Stacking Networks for Low-Resource Chinese Word Segmentation with Transfer Learning—0
Dependency-based Gated Recursive Neural Network for Chinese Word Segmentation—0
Discriminative Boosting from Dictionary and Raw Text -- A Novel Approach to Build A Chinese Word Segmenter—0
Combine CRF and MMSEG to Boost Chinese Word Segmentation in Social Media—0
DM\_NLP at SemEval-2018 Task 8: neural sequence labeling with linguistic features—0
Domain Adaptation for CRF-based Chinese Word Segmentation using Free Annotations—0
Addressing Domain Adaptation for Chinese Word Segmentation with Global Recurrent Structure—0
Effective Document-Level Features for Chinese Patent Word Segmentation—0
Automatic Adaptation of Annotations—0
Empirical Study of Unsupervised Chinese Word Segmentation Methods for SMT on Large-scale Corpora—0
Enhancement of Feature Engineering for Conditional Random Field Learning in Chinese Word Segmentation Using Unlabeled Data—0
Enhancing Chinese Word Segmentation via Pseudo Labels for Practicability—0
Enhancing Statistical Machine Translation with Character Alignment—0
Entropy-based Training Data Selection for Domain Adaptation—0
Exploring Deterministic Constraints: from a Constrained English POS Tagger to an Efficient ILP Solution to Chinese Word Segmentation—0
Exploring Mental Lexicon in an Efficient and Economic Way: Crowdsourcing Method for Linguistic Experiments—0
Exploring Representations from Unlabeled Data with Co-training for Chinese Word Segmentation—0
BERT Meets Chinese Word Segmentation—0
A More Efficient Chinese Named Entity Recognition base on BERT and Syntactic Analysis—0
Bidirectional LSTM-CRF Attention-based Model for Chinese Word Segmentation—0
A New Recurrent Neural CRF for Learning Non-linear Edge Features—0
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