Chinese Text Classification Based on Domain Ontology and SVM
Through choosing concept feature space which replaces the traditional keyword feature space, using domain ontology to adjust the feature weights of domain text, using SVM algorithm, the paper constructs a new Chinese text classification semantic model. The new model has been made use of to carry out a text classification experiment about computer domain and non-computer domain. The results show that domain ontology has a great effect on domain text classification and the accuracy of classification has been improved compared with the improved TFIOF method.
Domain ontology SVM Text classification
Guixi Zhang Jianzhuo Yan Liying Fang
School of Electronic Information and Control Engineering, Beijing University of Technology Beijing 100124, China
国际会议
2011 International Conference on Information and Industrial Electronics(2011年信息与工业电子国际会议 ICIIE 2011)
成都
英文
123-126
2011-01-14（万方平台首次上网日期，不代表论文的发表时间）