%A Hu Zewen, Wang Xiaoyue, Bai Rujiang %T Study on Text Classification Model Based on SUMO and WordNet Ontology Integration %0 Journal Article %D 2011 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.1003-3513.2011.01.05 %P 31-38 %V 27 %N 1 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_3329.shtml} %8 2011-01-25 %X

Aiming at the existing problems in the traditional text classification methods and the current semantic classification methods, a new text classification model based on SUMO and WordNet Ontology integration is proposed. This model utilizes the mapping relations between WordNet synsets and SUMO Ontology concepts to map terms in document-words vector space into the corresponding concepts in Ontology, and forms document-concepts vector space to classify texts automatically. The experiment results show that the proposed method can greatly decrease the dimensionality of vector space and improve the text classification performance.