{"title":"基于支持向量机的维吾尔语文本分类及其性能分析","authors":"Palidan Tuerxun, Dingyi Fang, Hamdulla Askar","doi":"10.14257/IJMUE.2015.10.4.27","DOIUrl":null,"url":null,"abstract":"This paper mainly explores the use of Support Vector Machines (SVMs) for Uyghur text classification, presents the process of text categorization: Text preprocessing, feature dimensionality reduction, representation method and classification of text features etc., discusses the SVMs classification algorithm in the application of Uyghur text classification. Focus on the construction of text categorization model and its procedures. Experiment results show that training by using the selected training data with the guarantee of the performance of the classifier, has higher efficiency than other nearest neighbor classifier (KNN), Naive Bayes (NB) classifier with increased accuracy.","PeriodicalId":162936,"journal":{"name":"International Conference on Multimedia and Ubiquitous Engineering","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The SVM based Uyghur Text Classification and its Performance Analysis\",\"authors\":\"Palidan Tuerxun, Dingyi Fang, Hamdulla Askar\",\"doi\":\"10.14257/IJMUE.2015.10.4.27\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper mainly explores the use of Support Vector Machines (SVMs) for Uyghur text classification, presents the process of text categorization: Text preprocessing, feature dimensionality reduction, representation method and classification of text features etc., discusses the SVMs classification algorithm in the application of Uyghur text classification. Focus on the construction of text categorization model and its procedures. Experiment results show that training by using the selected training data with the guarantee of the performance of the classifier, has higher efficiency than other nearest neighbor classifier (KNN), Naive Bayes (NB) classifier with increased accuracy.\",\"PeriodicalId\":162936,\"journal\":{\"name\":\"International Conference on Multimedia and Ubiquitous Engineering\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Conference on Multimedia and Ubiquitous Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14257/IJMUE.2015.10.4.27\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Multimedia and Ubiquitous Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14257/IJMUE.2015.10.4.27","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The SVM based Uyghur Text Classification and its Performance Analysis
This paper mainly explores the use of Support Vector Machines (SVMs) for Uyghur text classification, presents the process of text categorization: Text preprocessing, feature dimensionality reduction, representation method and classification of text features etc., discusses the SVMs classification algorithm in the application of Uyghur text classification. Focus on the construction of text categorization model and its procedures. Experiment results show that training by using the selected training data with the guarantee of the performance of the classifier, has higher efficiency than other nearest neighbor classifier (KNN), Naive Bayes (NB) classifier with increased accuracy.