Abstract
An important property of Context-Free Programmed Grammars (CFPG) is that some context-sensitive Languages can be generated by CFPG. To infer a special class of CFPG for syntactic pattern recognition is the motivation of this paper. First an one-dimensional string is transformed into a corresponding binary tree. Then in terms of the structure of subtrees, and the semantic rules corresponding to the context-free productions, a method for the inference of Context-free Programmed Grammar is presented. Inference of Stochastic Context-Free Programmed Grammar (STCFPG) by the maximum-likelihood estimate approach is also discussed.
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This work was supported in part by the NSF Grant ECS 78-16970.
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Tai, J.W., Fu, K.S. Inference of a class of CFPG by means of semantic rules. International Journal of Computer and Information Sciences 11, 1–23 (1982). https://doi.org/10.1007/BF00993198
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DOI: https://doi.org/10.1007/BF00993198