Abstract
This paper explores the techniques of utilizing N-gram information to categorize Chinese text documents hierarchically so that the classifier can shake off the burden of large dictionaries and complex segmentation processing, and subsequently be domain and time independent. A hierarchical Chinese text classifier is implemented. Experimental results show that hierarchically classifying Chinese text documents based N-grams can achieve satisfactory performance and outperforms the other traditional Chinese text classifiers.
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Guan, J., Zhou, S. (2003). Hierarchical Classification of Chinese Documents Based on N-grams. In: Sembok, T.M.T., Zaman, H.B., Chen, H., Urs, S.R., Myaeng, SH. (eds) Digital Libraries: Technology and Management of Indigenous Knowledge for Global Access. ICADL 2003. Lecture Notes in Computer Science, vol 2911. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24594-0_66
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DOI: https://doi.org/10.1007/978-3-540-24594-0_66
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20608-8
Online ISBN: 978-3-540-24594-0
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