Abstract
This paper presents an effective concept-based document classification system, which can efficiently classify Korean documents through the thesaurus tool. The thesaurus tool is the information extractor that acquires the meanings of document terms from the thesaurus. It supports effective document classification with the acquired meanings. The system uses the concept-probability vector to represent the meanings of the terms. Because the category of the document depends on the meanings than the terms, even though the size of the vector is small, the system can classify the document without degradation of the performance. The system uses the small concept-probability vector so that it can save the time and space for document classification. The experimental results suggest that the presented system with the thesaurus tool can effectively classify the documents.
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Kang, HK., Hwang, YG., Ryu, PM. (2004). An Effective Document Classification System Based on Concept Probability Vector. In: Chi, CH., Lam, KY. (eds) Content Computing. AWCC 2004. Lecture Notes in Computer Science, vol 3309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30483-8_56
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DOI: https://doi.org/10.1007/978-3-540-30483-8_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23898-0
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