Hyper-Gated Recurrent Neural Networks for Chinese Word Segmentation

2018 ◽  
pp. 443-455
Author(s):  
Zhan Shi ◽  
Xinchi Chen ◽  
Xipeng Qiu ◽  
Xuanjing Huang
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Word Segmentation ◽  
Chinese Word ◽  
Chinese Word Segmentation

Chinese Word Segmentation Based on the First Kind of Spline Weight Function Neural Networks

2014 ◽  
Vol 513-517 ◽  
pp. 683-686 ◽  
Author(s):  
Dai Yuan Zhang ◽  
Yan Xu
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Information Technology ◽  
Weight Function ◽  
English Word ◽  
Word Segmentation ◽  
Chinese Word ◽  
Chinese Word Segmentation ◽  
Continuous Development ◽  
Chinese Writing

With the continuous development of information technology, word segmentation technology becomes an important link in dealing with the increasing amount of information conveniently. Different from English word segmented by spaces, Chinese writing is continuous, and there is no space between words, this brings a lot of trouble to word segmentation. In this article, through the analysis of different property of words to get a code that can be used for training and combined it with the first kind of spline weight function neural network, then by training a large number of existing rules encoding to generate a study method that can divide the statement correctly.

scholarly journals Segmenting Chinese Microtext: Joint Informal-Word Detection and Segmentation with Neural Networks

2017 ◽  
Author(s):  
Meishan Zhang ◽  
Guohong Fu ◽  
Nan Yu
Keyword(s):  
Neural Networks ◽  
State Of The Art ◽  
Joint Model ◽  
Word Segmentation ◽  
Chinese Word ◽  
Chinese Word Segmentation ◽  
Training Corpus ◽  
Standard Testing ◽  
Proposed Model ◽  
Word Detection

State-of-the-art Chinese word segmentation systems typically exploit supervised modelstrained on a standard manually-annotated corpus,achieving performances over 95% on a similar standard testing corpus.However, the performances may drop significantly when the same models are applied onto Chinese microtext.One major challenge is the issue of informal words in the microtext.Previous studies show that informal word detection can be helpful for microtext processing.In this work, we investigate it under the neural setting, by proposing a joint segmentation model that integrates the detection of informal words simultaneously.In addition, we generate training corpus for the joint model by using existing corpus automatically.Experimental results show that the proposed model is highly effective for segmentation of Chinese microtext.

Sign in / Sign up

Export Citation Format

Share Document