Results 21 to 30 of about 62,130 (288)

Unsupervised Chinese Word Segmentation with BERT Oriented Probing and Transformation

Findings, 2022
Word Segmentation is a fundamental step for understanding Chinese language. Previous neural approaches for unsupervised Chinese Word Segmentation (CWS) only exploits shallow semantic information, which can miss important context.
Wei Li, Y. Song, Qi Su, Yanqiu Shao
semanticscholar   +1 more source

Pre-training with Meta Learning for Chinese Word Segmentation

North American Chapter of the Association for Computational Linguistics, 2021
Recent researches show that pre-trained models (PTMs) are beneficial to Chinese Word Segmentation (CWS). However, PTMs used in previous works usually adopt language modeling as pre-training tasks, lacking task-specific prior segmentation knowledge and ...
Zhen Ke, Liang Shi, Songtao Sun, Erli Meng, Bin Wang, Xipeng Qiu   +5 more
semanticscholar   +1 more source

Chinese Word Segmentation Based on Self‐Learning Model and Geological Knowledge for the Geoscience Domain

Earth and Space Science, 2021
Chinese word segmentation (CWS) is the foundational work of geological report text mining and has an important influence on various tasks, such as named entity recognition and relation extraction.
Wenjia Li, K. Ma, Qinjun Qiu, Liang Wu, Zhong Xie, Sanfeng Li, Siqiong Chen   +6 more
semanticscholar   +1 more source

Research on performance variations of classifiers with the influence of pre-processing methods for Chinese short text classification.

PLoS ONE, 2023
Text pre-processing is an important component of a Chinese text classification. At present, however, most of the studies on this topic focus on exploring the influence of preprocessing methods on a few text classification algorithms using English text ...
Dezheng Zhang, Jing Li, Yonghong Xie, Aziguli Wulamu   +3 more
doaj   +1 more source

Improving Chinese Word Segmentation with Wordhood Memory Networks

Annual Meeting of the Association for Computational Linguistics, 2020
Contextual features always play an important role in Chinese word segmentation (CWS). Wordhood information, being one of the contextual features, is proved to be useful in many conventional character-based segmenters.
Yuanhe Tian, Yan Song, Fei Xia, Tong Zhang, Yonggang Wang   +4 more
semanticscholar   +1 more source

The Extended Simple View of Reading in Adult Learners of Chinese as a Second Language

Frontiers in Psychology, 2022
The Simple View of Reading (SVR) designates that reading comprehension is the product of decoding and listening comprehension and this conclusion has been supported by studies on school-aged native and nonnative speakers.
Meiling Hao, Meiling Hao, Xiaoping Fang, Zhenzhen Sun, Zhenzhen Sun, Youyi Liu   +5 more
doaj   +1 more source

Joint Chinese Word Segmentation and Part-of-speech Tagging via Two-way Attentions of Auto-analyzed Knowledge

Annual Meeting of the Association for Computational Linguistics, 2020
Chinese word segmentation (CWS) and part-of-speech (POS) tagging are important fundamental tasks for Chinese language processing, where joint learning of them is an effective one-step solution for both tasks.
Yuanhe Tian, Yan Song, Xiang Ao, Fei Xia, Xiaojun Quan, Tong Zhang, Yonggang Wang   +6 more
semanticscholar   +1 more source

Lexicon-Based Graph Convolutional Network for Chinese Word Segmentation

Conference on Empirical Methods in Natural Language Processing, 2021
Precise information of word boundary can alleviate the problem of lexical ambiguity to improve the performance of natural language processing (NLP) tasks. Thus, Chinese word segmentation (CWS) is a fundamental task in NLP.
Kaiyu Huang, Haopeng Yu, Junpeng Liu, Wei Liu, Jingxiang Cao, Degen Huang   +5 more
semanticscholar   +1 more source

Can Word-Word Space Facilitate L2 Chinese Reading: Evidence From the Two Empirical Studies by Advanced L2 Learners of Mandarin Chinese

SAGE Open, 2021
The purpose of this article aims to analyze the effect of word-word space in written Chinese to advanced non-native speakers when they read and process Mandarin texts.
Ken Chen, Lei Gu, Hongshan Zuo, Qiaoyan Bai   +3 more
doaj   +1 more source

State-of-the-art Chinese Word Segmentation with Bi-LSTMs [PDF]

Conference on Empirical Methods in Natural Language Processing, 2018
A wide variety of neural-network architectures have been proposed for the task of Chinese word segmentation. Surprisingly, we find that a bidirectional LSTM model, when combined with standard deep learning techniques and best practices, can achieve ...
Ji Ma, Kuzman Ganchev, David Weiss
semanticscholar   +1 more source