The research of estimation model for the correlativity between words in Chinese text

被引:0
|
作者
Zhang, YS [1 ]
Cao, YD [1 ]
Chen, LC [1 ]
机构
[1] Beijing Inst Technol, Dept Comp Sci & Engn, Beijing 100081, Peoples R China
关键词
context correlativity; language environment related model; bi-orderly-neighbor model; mutual information;
D O I
暂无
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
The analysis and use of the relation between words in Chinese text by statistical method is discussed in this article. After understanding the importance of the relation between words we investigated the characteristics of measurement models such as mutual information and related degree, and constructed a cascade estimation model which is used to describe the bi-orderly-neighbor between neighboring words in Chinese. Then, based on the characteristic of the Chinese text proof distance information between words and context information of current word were combined with N-gram model, and a novel model of correlativity between words based on language environment is present. Finally, the two models were applied in Chinese text automatic proof and corresponding experiment data and results are presented. Results show that the language environment related model can describe the relation between words better than other models such as mutual information or related degree, and indicate a good effect in the automatic defection of Chinese text errors.
引用
收藏
页码:1174 / 1178
页数:5
相关论文
共 50 条
  • [21] Research on Toponym resolution in Chinese text
    Tang, Xuri
    Chen, Xiaohe
    Zhang, Xueying
    [J]. Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University, 2010, 35 (08): : 930 - 935
  • [22] Challenges in Chinese text similarity research
    Wang, Xiuhong
    Ju, Shiguang
    Wu, Shengli
    [J]. 2008 INTERNATIONAL SYMPOSIUM ON INFORMATION PROCESSING AND 2008 INTERNATIONAL PACIFIC WORKSHOP ON WEB MINING AND WEB-BASED APPLICATION, 2008, : 297 - +
  • [23] The research of the most short-path's Chinese words segmentation words model based on N1
    Lin, Hongwei
    Lin, Zhuying
    [J]. 2009 INTERNATIONAL CONFERENCE ON NETWORKING AND DIGITAL SOCIETY, VOL 2, PROCEEDINGS, 2009, : 271 - 274
  • [24] Do Important Words in Bag-of-Words Model of Text Relatedness Help?
    Islam, Aminul
    Milios, Evangelos
    Keselj, Vlado
    [J]. TEXT, SPEECH, AND DIALOGUE (TSD 2015), 2015, 9302 : 569 - 577
  • [25] Painting words: aesthetics and the relationship between image and text
    Huen, Antony
    [J]. EARLY POPULAR VISUAL CULTURE, 2022, 20 (01) : 85 - 87
  • [26] Distinction between handwritten and machine-printed text based on the bag of visual words model
    Zagoris, Konstantinos
    Pratikakis, Ioannis
    Antonacopoulos, Apostolos
    Gatos, Basilis
    Papamarkos, Nikos
    [J]. PATTERN RECOGNITION, 2014, 47 (03) : 1051 - 1062
  • [28] Generating Lexico Pattern for Dimensioning of Chinese Separable Verb-object Words in Chinese Text
    Huang, Kaiyan
    Li, Yun
    Ren, Fuji
    [J]. IEEE NLP-KE 2008: PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NATURAL LANGUAGE PROCESSING AND KNOWLEDGE ENGINEERING, 2008, : 9 - 14
  • [29] Research on Coherence Structure Construction for Chinese Text
    Chen, Yanmin
    Lou, Xizhong
    Zhan, Jingwen
    Wu, Shanqiang
    [J]. ADVANCED MATERIALS AND COMPUTER SCIENCE, PTS 1-3, 2011, 474-476 : 1648 - +
  • [30] Research on the Attitude towards Lettered-words in Chinese
    潘正华
    [J]. 科技视界, 2014, (09) : 161 - 162