Abstract
This paper presents a new Chinese question taxonomy respectively from approach and semantic viewpoints, and a SVM classification algorithm based on multiple features and hybrid feature weighting. The experimental results show that: (1) Lexical semantic features and structural features are the guarantee of high performance of question classification; (2) The contribution of dependency relation extracted from our current parser is no better than that of Bi-gram. (3) Our proposed feature weighting is effective for question classification.
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Wu, Y., Zhao, J., Xu, B. (2005). Chinese Question Classification from Approach and Semantic Views. In: Lee, G.G., Yamada, A., Meng, H., Myaeng, S.H. (eds) Information Retrieval Technology. AIRS 2005. Lecture Notes in Computer Science, vol 3689. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11562382_38
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DOI: https://doi.org/10.1007/11562382_38
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29186-2
Online ISBN: 978-3-540-32001-2
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