Grammatical Inference (Lecture Notes in Computer Science) de Vasant Honavar

Grammatical Inference: 4th International Colloquium, ICGI-98, Ames, Iowa, USA, July 12-14, 1998, Proceedings: Lecture Notes in Computer Science, cartea 1433

Vasant Honavar

Giora Slutzki

This book constitutes the refereed proceedings of the Fourth International Colloquium on Grammatical Inference, ICGI-98, held in Ames, Iowa, in July 1998.
The 23 revised full papers were carefully reviewed and selected for inclusion in the book from a total of 35 submissions. The book addresses a wide range of grammatical inference theory such as automata induction, grammar induction, automatic language acquisition, etc. as well as a variety of applications in areas like syntactic pattern recognition, adaptive intelligent agents, diagnosis, computational biology, data mining, and knowledge discovery.

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Specificații

ISBN-13: 9783540647768
ISBN-10: 3540647767
Pagini: 288
Ilustrații: XI, 277 p.
Dimensiuni: 155 x 235 x 15 mm
Greutate: 0.41 kg
Ediția:1998
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Berlin, Heidelberg, Germany

Cuprins

Results of the Abbadingo one DFA learning competition and a new evidence-driven state merging algorithm.- Learning k-variable pattern languages efficiently stochastically finite on average from positive data.- Meaning helps learning syntax.- A polynomial time incremental algorithm for learning DFA.- The data driven approach applied to the OSTIA algorithm.- Grammar model and grammar induction in the system NL PAGE.- Approximate learning of random subsequential transducers.- Learning stochastic finite automata from experts.- Learning a deterministic finite automaton with a recurrent neural network.- Applying grammatical inference in learning a language model for oral dialogue.- Real language learning.- A stochastic search approach to grammar induction.- Transducer-learning experiments on language understanding.- Locally threshold testable languages in strict sense: Application to the inference problem.- Learning a subclass of linear languages from positive structural information.- Grammatical inference in document recognition.- Stochastic inference of regular tree languages.- How considering incompatible state mergings may reduce the DFA induction search tree.- Learning regular grammars to model musical style: Comparing different coding schemes.- Learning a subclass of context-free languages.- Using symbol clustering to improve probabilistic automaton inference.- A performance evaluation of automatic survey classifiers.- Pattern discovery in biosequences.