ISBN: 978-981-09-5471-0 DOI: 10.18178/wcse.2015.04.128
Performance Analysis of Ad Hoc Classifiers for Categorization of Uyghur texts
Abstract— This paper starts from the characteristics and writing rules of Uyghur, have established a
relatively large text corpus which include 20 categories, 300 documents for each category. And
studied the KNN, Naive Bayes (NB), and SVM classification algorithms more thoroughly, which
have widely been used in domestic and foreign academic research fields, then classified the Uyghur
text by using these algorithms, and analyzed the performance of each algorithm separately. Finally,
some research directions on Uyghur text classification are also given in this paper.
Index Terms— Uyghur; text classification; stemming; classifier.
Palidan Tuerxun, Fang Dingyi
School of information and technology, Northwestern University, CHINA
Palidan Tuerxun, Fang Dingyi, Askar Hamdulla
School of Software, Xinjiang University CHINA
Cite: Palidan Tuerxun, Fang Dingyi, Askar Hamdulla, "Performance Analysis of Ad Hoc Classifiers for Categorization of Uyghur texts," 2015 The 5th International Workshop on Computer Science and Engineering-Information Processing and Control Engineering (WCSE 2015-IPCE), pp. 803-806, Moscow, Russia, April 15-17, 2015.