A Model of Probabilistic Parsing Automata 


Vol. 44,  No. 3, pp. 239-245, Mar.  2017


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  Abstract

Probabilistic grammar is used in natural language processing, and the parse result of the grammar has to preserve the probability of the original grammar. As for the representative parsing method, LL parsing and LR parsing, the former preserves the probability information of the original grammar, but the latter does not. A characteristic of a probabilistic parsing automaton has been studied; but, currently, the generating model of probabilistic parsing automata has not been known. The paper provides a model of probabilistic parsing automata based on the single state parsing automata. The generated automaton preserves the probability of the original grammar, so it is not necessary to test whether or not the automaton is probabilistic parsing automaton; defining a probability function for the automaton is not required. Additionally, an efficient automaton can be constructed by choosing an appropriate parameter.


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  Cite this article

[IEEE Style]

G. Lee, "A Model of Probabilistic Parsing Automata," Journal of KIISE, JOK, vol. 44, no. 3, pp. 239-245, 2017. DOI: .


[ACM Style]

Gyung-Ok Lee. 2017. A Model of Probabilistic Parsing Automata. Journal of KIISE, JOK, 44, 3, (2017), 239-245. DOI: .


[KCI Style]

이경옥, "확률파싱오토마타 모델," 한국정보과학회 논문지, 제44권, 제3호, 239~245쪽, 2017. DOI: .


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