西北师范大学学报（自然科学版）Issue(3)：48-53,6.
一种基于SVM-修正KNN 算法的哈萨克语文本分类
An approach to the text categorization of the Kazakh language based on SVM-modified KNN algorithm
摘要
Abstract
In order to get the Kazakh language text classification , according to the Kazakh language features , this paper presents the Kazakh stem extract principle , and implementes the Kazakh text preprocessing combined with DFR feature selection and VSM model . This paper proposes a SVM-modified KNN algorithm ,a large number of text categorization experiments are simulated on the own building data sets and the Xinjiang Daily Kazakh data sets respectively . The numerical experiment results show that the method in the Kazakh language text classification has a good classification performance , and its test performance is better than the SVM and KNN .关键词
词干提取/DFR/VSM/SVM-KNNKey words
stemming/DFR/VSM/SVM-KNN分类
信息技术与安全科学引用本文复制引用
古丽娜孜·艾力木江,孙铁利,乎西旦,特列克别克..一种基于SVM-修正KNN 算法的哈萨克语文本分类[J].西北师范大学学报（自然科学版）,2014,(3):48-53,6.基金项目
国家自然科学基金资助项目（61363066）；教育部博士点基金资助项目（20110043110011）；吉林省科技发展计划项目（20120302）；伊犁师范学院院级项目 （）
