Algorithm Research & Explore
|
3548-3552

Research on feature construction of Uyghur text sentiment classification

Raxida Turhuntay1,2
Wushour Slamu1
1. College of Information Science & Engineering, Xinjiang University, Urumqi 830046, China
2. College of Electronic & Information Engineering, Yili Normal University, Yili Xinjiang 835000, China

Abstract

Due to the lack of systematic research on the feature expression of Uyghur text sentiment classification, this paper used the traditional n-gram features as the basis to extract new features and combined features from Uyghur sentiment corpora on different scales, and used support vector machine(SVM) classifier to classify the corpora as positive and negative. Results indicated that, in the Uyghur text sentiment classification, the unigram features in the basic features have the best classification efficiency. The combination of unigram features and phrase features can further improve the classification efficiency. The best performance of the combined features, the classification accuracy is 1.78% higher than that of unigram. This paper first made a comprehensive evaluation of the classification performance of different features on a unified data set. The research results can be applied as a reference for future Uyghur sentiment classification research.

Foundation Support

国家“973”计划资助项目(2014CB340506)
国家自然科学基金资助项目(61363063)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.04.0378
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 12
Section: Algorithm Research & Explore
Pages: 3548-3552
Serial Number: 1001-3695(2019)12-006-3548-05

Publish History

[2019-12-05] Printed Article

Cite This Article

热西旦木·吐尔洪太, 吾守尔·斯拉木. 维吾尔文情感分类特征建设研究 [J]. 计算机应用研究, 2019, 36 (12): 3548-3552. (Raxida Turhuntay, Wushour Slamu. Research on feature construction of Uyghur text sentiment classification [J]. Application Research of Computers, 2019, 36 (12): 3548-3552. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.


Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)