Abstract
Complete parsing is difficult to meet the need of precision and recall rate in Chinese. To address this problem, a new model for shallow parsing of Chinese is presented in this paper. We adopt Church theory and carry on Chinese phrases recognition based on HMM; improve the precision rate of sentences separation by improving the observance probabilities of HMM model and making use of the context information of the Chinese sentences. At the same time, by studying the rules of Chinese sentence, we extract some rules useful for ambiguity elimination. The experimental result indicates that the model based on HMM has high precision and recall rate.
Supported by Foundation for Distinguished Young Talents in Higher Education of Guangdong, China Number:LYM09084.
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Weifa, Z., Wenliang, X. (2013). Shallow Parsing of Chinese Based on HMM Model. In: Du, Z. (eds) Intelligence Computation and Evolutionary Computation. Advances in Intelligent Systems and Computing, vol 180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31656-2_12
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DOI: https://doi.org/10.1007/978-3-642-31656-2_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31655-5
Online ISBN: 978-3-642-31656-2
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