IEEE Transactions on Pattern Analysis and Machine Intelligence
Procedure for quantitatively comparing the syntactic coverage of English grammars
HLT '91 Proceedings of the workshop on Speech and Natural Language
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Theoretical Computer Science - Special issue on algorithmic learning theory
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COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory
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Journal of the ACM (JACM)
Introduction To Automata Theory, Languages, And Computation
Introduction To Automata Theory, Languages, And Computation
Learning Context-Free Grammars with a Simplicity Bias
ECML '00 Proceedings of the 11th European Conference on Machine Learning
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ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
Learning Context-Free Grammars from Partially Structured Examples
ICGI '00 Proceedings of the 5th International Colloquium on Grammatical Inference: Algorithms and Applications
The EMILE 4.1 Grammar Induction Toolbox
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Incremental Learning of Context Free Grammars
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
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ICG! '96 Proceedings of the 3rd International Colloquium on Grammatical Inference: Learning Syntax from Sentences
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ALT '98 Proceedings of the 9th International Conference on Algorithmic Learning Theory
A study of grammatical inference
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Computational Linguistics - Special issue on using large corpora: II
A DOP model for semantic interpretation
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
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EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
ALLiS: a symbolic learning system for Natural Language Learning
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Unsupervised induction of stochastic context-free grammars using distributional clustering
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Coarse-to-fine n-best parsing and MaxEnt discriminative reranking
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Effective self-training for parsing
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
A psychologically plausible and computationally effective approach to learning syntax
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Limitations of current grammar induction algorithms
ACL '07 Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop
Statistical parsing with a context-free grammar and word statistics
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
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The high complexity of natural language and the huge amount of human and temporal resources necessary for producing the grammars lead several researchers in the area of Natural Language Processing to investigate various solutions for automating grammar generation and updating processes. Many algorithms for Context-Free Grammar inference have been developed in the literature. This paper provides a survey of the methodologies for inferring context-free grammars from examples, developed by researchers in the last decade. After introducing some preliminary definitions and notations concerning learning and inductive inference, some of the most relevant existing grammatical inference methods for Natural Language are described and classified according to the kind of presentation (if text or informant) and the type of information (if supervised, unsupervised, or semi-supervised). Moreover, the state of the art of the strategies for evaluation and comparison of different grammar inference methods is presented. The goal of the paper is to provide a reader with introduction to major concepts and current approaches in Natural Language Learning research.