• Journal of KIISE:Software and Applications
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• v.41 no.7
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• pp.518-522
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• 2014

A single state parsing automaton has the characteristics of the decision of actions which do not depend on the history of the parsing paths but on the current state. The single state parsing automaton hence has the advantage of the reduced parsing time and a small memory requirement compared to those of the conventional LR automaton. However, currently, the grammar classes generating single state parsing automata have not been known. This paper deals with the grammar classes generating single state parsing automata; in addition, this paper gives the generating method of single state parsing automata of the grammar classes.

• Journal of KIISE:Software and Applications
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• v.35 no.11
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• pp.701-704
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• 2008

A general automaton allows multiple input transitions, so a special treatment is required when the history of transitions is needed. An LR automaton keeps the past transitions in the stack to use them during parsing. On the other hand, when each state in an automaton contains in itself the past transition history, the trace overhead of past transitions is unnecessary. The paper suggests a single state parsing automaton that does not depend on the past transitions. The applicable grammar class is less than LR grammars, but each state in a new automaton contains the past information, so the tracing of the history is not required compared to LR automaton.

• Journal of KIISE
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• v.44 no.3
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• pp.239-245
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• 2017

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.