Building probabilistic models for natural language
Building probabilistic models for natural language
Inducing Probabilistic Grammars by Bayesian Model Merging
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
A minimum description length approach to grammar inference
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing
Unsupervised language acquisition
Unsupervised language acquisition
Smoothing a probablistic lexicon via syntactic transformations
Smoothing a probablistic lexicon via syntactic transformations
Computational Linguistics
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
PCFG models of linguistic tree representations
Computational Linguistics
Lexical rules in constraint-based grammars
Computational Linguistics
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Three generative, lexicalised models for statistical parsing
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
An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Three new probabilistic models for dependency parsing: an exploration
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Parameter estimation for probabilistic finite-state transducers
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
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
Head-Driven Statistical Models for Natural Language Parsing
Computational Linguistics
Shared logistic normal distributions for soft parameter tying in unsupervised grammar induction
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Name phylogeny: a generative model of string variation
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
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This paper proposes a novel class of PCFG parameterizations that support linguistically reasonable priors over PCFGs. To estimate the parameters is to discover a notion of relatedness among context-free rules such that related rules tend to have related probabilities. The prior favors grammars in which the relationships are simple to describe and have few major exceptions. A basic version that bases relatedness on weighted edit distance yields superior smoothing of grammars learned from the Penn Treebank (20% reduction of rule perplexity over the best previous method).