Grammatical inference : 4th International Colloquium, ICGI-98 Ames, Iowa, USA, July 12-14, 1998 : proceedings

書誌事項

Grammatical inference : 4th International Colloquium, ICGI-98 Ames, Iowa, USA, July 12-14, 1998 : proceedings

Vasant Honavar, Giora Slutzki (eds.)

(Lecture notes in computer science, 1433 . Lecture notes in artificial intelligence)

Springer, c1998

大学図書館所蔵 件 / 36

この図書・雑誌をさがす

注記

Includes bibliographical references and index

内容説明・目次

内容説明

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.

目次

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.

「Nielsen BookData」 より

関連文献: 1件中  1-1を表示

詳細情報

ページトップへ