Abstract
Identifying comparative sentences in natural language is an important step for extracting comparative relations. To our knowledge, there is no research on identifying Chinese comparative sentences automatically. This paper first defines the problem of Chinese comparative sentence identification, and then proposes to use several classifiers to classify a Chinese sentence into either “comparative” or not. Various linguistic and statistical features have been explored, such as keywords and sequential patterns. Experimental results demonstrate the good effectiveness of the sequential patterns, i.e. the classifiers with sequential patterns can significantly outperform the traditional term-based classifier. We also empirically investigate the important factors that affect classification performance.
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Huang, X., Wan, X., Yang, J., Xiao, J. (2008). Learning to Identify Comparative Sentences in Chinese Text. In: Ho, TB., Zhou, ZH. (eds) PRICAI 2008: Trends in Artificial Intelligence. PRICAI 2008. Lecture Notes in Computer Science(), vol 5351. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89197-0_20
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DOI: https://doi.org/10.1007/978-3-540-89197-0_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89196-3
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