Learning probabilistic automata with variable memory length
COLT '94 Proceedings of the seventh annual conference on Computational learning theory
On the learnability of discrete distributions
STOC '94 Proceedings of the twenty-sixth annual ACM symposium on Theory of computing
Bayesian learning of probabilistic language models
Bayesian learning of probabilistic language models
On the learnability and usage of acyclic probabilistic finite automata
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Machine Learning
Information Retrieval
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
ICGI '98 Proceedings of the 4th International Colloquium on Grammatical Inference
Learning Stochastic Regular Grammars by Means of a State Merging Method
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Improving Probabilistic Grammatical Inference Core Algorithms with Post-processing Techniques
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
An Integrated Statistical Model for Tagging and Chunking Unrestricted Text
TDS '00 Proceedings of the Third International Workshop on Text, Speech and Dialogue
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
TnT: a statistical part-of-speech tagger
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Bagging and boosting a treebank parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
Incremental finite-state parsing
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Part-of-speech tagging using a Variable Memory Markov model
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Introduction to the CoNLL-2000 shared task: chunking
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
A context sensitive maximum likelihood approach to chunking
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Use of support vector learning for chunk identification
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Probabilistic Finite-State Machines-Part II
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Pruning of Probabilistic Automata
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Position Models and Language Modeling
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
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This paper presents an application of grammatical inference to the task of shallow parsing. We first learn a deterministic probabilistic automaton that models the joint distribution of Chunk (syntactic phrase) tags and Part-of-speech tags, and then use this automaton as a transducer to find the most likely chunk tag sequence using a dynamic programming algorithm. We discuss an efficient means of incorporating lexical information, which automatically identifies particular words that are useful using a mutual information criterion, together with an application of bagging that improve our results. Though the results are not as high as comparable techniques that use models with a fixed structure, the models we learn are very compact and efficient.