The inclusion problem for some subclasses of context-free languages
Theoretical Computer Science
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ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
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AII '89 Proceedings of the International Workshop on Analogical and Inductive Inference
Estimation of probabilistic context-free grammars
Computational Linguistics
On a Construction of Context-free Grammars
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Polynomial Identification in the Limit of Substitutable Context-free Languages
The Journal of Machine Learning Research
A Polynomial Algorithm for the Inference of Context Free Languages
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
Identification in the Limit of k,l-Substitutable Context-Free Languages
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
Another look at indirect negative evidence
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ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
Distributional learning of some context-free languages with a minimally adequate teacher
ICGI'10 Proceedings of the 10th international colloquium conference on Grammatical inference: theoretical results and applications
A learnable representation for syntax using residuated lattices
FG'09 Proceedings of the 14th international conference on Formal grammar
PAC-learning unambiguous NTS languages
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Towards general algorithms for grammatical inference
ALT'10 Proceedings of the 21st international conference on Algorithmic learning theory
Towards dual approaches for learning context-free grammars based on syntactic concept lattices
DLT'11 Proceedings of the 15th international conference on Developments in language theory
A language theoretic approach to syntactic structure
MOL'11 Proceedings of the 12th biennial conference on The mathematics of language
Distributional learning of simple context-free tree grammars
ALT'11 Proceedings of the 22nd international conference on Algorithmic learning theory
Integration of the dual approaches in the distributional learning of context-free grammars
LATA'12 Proceedings of the 6th international conference on Language and Automata Theory and Applications
Logical grammars, logical theories
LACL'12 Proceedings of the 7th international conference on Logical Aspects of Computational Linguistics
Four one-shot learners for regular tree languages and their polynomial characterizability
Theoretical Computer Science
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The Syntactic Concept Lattice is a residuated lattice based on the distributional structure of a language; the natural representation based on this is a context sensitive formalism. Here we examine the possibility of basing a context free grammar (CFG) on the structure of this lattice; in particular by choosing non-terminals to correspond to concepts in this lattice. We present a learning algorithm for context free grammars which uses positive data and membership queries, and prove its correctness under the identification in the limit paradigm. Since the lattice itself may be infinite, we consider only a polynomially bounded subset of the set of concepts, in order to get an efficient algorithm. We compare this on the one hand to learning algorithms for context free grammars, where the non-terminals correspond to congruence classes, and on the other hand to the use of context sensitive techniques such as Binary Feature Grammars and Distributional Lattice Grammars. The class of CFGs that can be learned in this way includes inherently ambiguous and thus non-deterministic languages; this approach therefore breaks through an important barrier in CFG inference.