Abstract
LIGHT, the parsing system for typed-unification grammars [3], was recently extended so to allow the automate learning of attribute/feature paths values. Motivated by the logic design of these grammars [2], the learning strategy we adopted is inspired by Inductive Logic Programming [5]; we proceed by searching through hypothesis spaces generated by logic transformations of the input grammar. Two procedures — one for generalisation, the other for specialisation — are in charge with the creation of these hypothesis spaces.
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Ciortuz, L. (2002). A Framework for Inductive Learning of Typed-Unification Grammars. In: Adriaans, P., Fernau, H., van Zaanen, M. (eds) Grammatical Inference: Algorithms and Applications. ICGI 2002. Lecture Notes in Computer Science(), vol 2484. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45790-9_26
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DOI: https://doi.org/10.1007/3-540-45790-9_26
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