Abstract
This paper presents a hybrid approach to Chinese abbreviation expansion. In this study, each short-form in Chinese text is assumed to be created by the method of reduction and the method of elimination or generalization, respectively. A mapping table between short words and long words and a dictionary of non-reduced short-form/full-form pairs are thus applied to generate the respective expansion candidates. Then, a hidden Markov model (HMM) based disambiguation is employed to rank these candidates and select a proper expansion for each ambiguous abbreviation. In order to improve expansion accuracy, some linguistic knowledge like discourse information and abbreviation patterns are further employed to double-check the expanded results and revise some error expansions if any. The proposed approach was evaluated on an abbreviation-expanded corpus built from the Peking University Corpus. The results showed that a recall of 83.8% and a precision of 86.3% can be achieved on average for different types of Chinese abbreviations.
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© 2006 Springer-Verlag Berlin Heidelberg
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Fu, G., Luke, KK., Zhang, M., Zhou, G. (2006). A Hybrid Approach to Chinese Abbreviation Expansion. In: Matsumoto, Y., Sproat, R.W., Wong, KF., Zhang, M. (eds) Computer Processing of Oriental Languages. Beyond the Orient: The Research Challenges Ahead. ICCPOL 2006. Lecture Notes in Computer Science(), vol 4285. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11940098_29
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DOI: https://doi.org/10.1007/11940098_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49667-0
Online ISBN: 978-3-540-49668-7
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