Abstract
This paper presents a method of processing Chinese syntactic category ambiguity with support vector machines (SVMs): extracting the word itself, candidate part-of-speech (POS) tags, the pair of candidate POS tags and their probability and context information as the features of the word vector. A training set is established. The machine learning models of disambiguation based on support vector machines are obtained using polynomial kernel functions. The testing results show that this method is efficient. The paper also gives the results obtained with neural networks for comparison.
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References
Murata, M., Ma, Q., Isahara, H.: Part of Speech Tagging in Thai Language Using Support Vector Machine. In: Isahara, H., Ma, Q. (eds.) Proceedings of the Second Workshop on Natural Language Processing and Neural Networks, Japan NLPRS 2001, Tokyo, pp. 24–30 (2001)
Weischedel, R., Meteer, M., Schwartz, R., Ramshaw, L., Palmucci, J.: Coping with Ambiguity and Unknown Words through Probabilistic Models. Computational Linguistics 19, 359–382 (1993)
Huang, D.G., Zhang, L.J., Zhang, Y.L., Yang, Y.S.: Disambiguation Mechanism Using Rule Techniques and Statistics Techniques. Mini-Micro Systems 24, 1252–1255 (2003)
Wei, O., Wu, J., Sun, Y.: Analysis and Improvement of Statistic-Based-Chinese Part-of- Speech Tagging. Journal of Software 4, 473–480 (2000)
Yu, X., Zhu, F.S.: Chinese Syntactic Category Disambiguation with the Neural Networks. Computer Research & Development 4, 367–369 (1998)
Vapnik, V.N.: The Nature of Statistical Learning Theory. Springer, Berlin (1995)
Joachims, T.: Text Categorization with Support Vector Machines: Learning with Many Relevant Features. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol. 1398, pp. 137–142. Springer, Heidelberg (1998)
Li, L.S., Chen, C.R., Huang, D.G., Yang, Y.S.: Identifying Pronunciation-Translated Names from Chinese Texts Based on Support Vector Machines. In: Yin, F.-L., Wang, J., Guo, C.A. (eds.) ISNN 2004. LNCS, vol. 3173, pp. 983–988. Springer, Heidelberg (2004)
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Li, L., Li, L., Huang, D., Song, H. (2005). Chinese Syntactic Category Disambiguation Using Support Vector Machines. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_39
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DOI: https://doi.org/10.1007/11427445_39
Publisher Name: Springer, Berlin, Heidelberg
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