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New Technology of Library and Information Service  2011, Vol. 27 Issue (1): 31-38    DOI: 10.11925/infotech.1003-3513.2011.01.05
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Study on Text Classification Model Based on SUMO and WordNet Ontology Integration
Hu Zewen, Wang Xiaoyue, Bai Rujiang
Institute of Scientific & Technical Information, Shandong University of Technology, Zibo 255049, China
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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.

Key wordsSUMO Ontology      WordNet      Ontology integration      Text classification model      Word vector space      Concept vector space     
Received: 02 November 2010      Published: 12 February 2011

G250 TP391


Cite this article:

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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