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.
胡泽文, 王效岳, 白如江. 基于SUMO和WordNet本体集成的文本分类模型研究[J]. 现代图书情报技术, 2011, 27(1): 31-38.
Hu Zewen, Wang Xiaoyue, Bai Rujiang. Study on Text Classification Model Based on SUMO and WordNet Ontology Integration. New Technology of Library and Information Service, 2011, 27(1): 31-38.
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