Abstract
In the paper we present the method of the generalisation of a language sample for grammatical inference of quasi context-sensitive GDPLL(k) grammars. GDPLL(k) grammars and parsers have been developed as an efficient tool for syntactic pattern recognition: the grammars are characterised by very good discriminative properties and the parser for the grammars is of the linear computational complexity. Nevertheless, one of the main problems of practical application of GDPLL(k) grammars in syntactic pattern recognition systems consists in difficulties in defining the grammar from the sample of a pattern language. The method which we describe in the paper is an important element of the solution of this problem.
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Jurek, J. (2007). Generalisation of a Language Sample for Grammatical Inference of GDPLL(k) Grammars. In: Kurzynski, M., Puchala, E., Wozniak, M., Zolnierek, A. (eds) Computer Recognition Systems 2. Advances in Soft Computing, vol 45. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75175-5_35
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DOI: https://doi.org/10.1007/978-3-540-75175-5_35
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