Grammatical Inference: Algorithms and Applications

5th International Colloquium, ICGI 2000, Lisbon, Portugal, September 11-13, 2000 Proceedings

Paperback Engels 2000 2000e druk 9783540410119
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Samenvatting

The Fifth International Colloquium on Grammatical Inference (ICGI-2000) was heldinLisbononSeptember11–13th,2000.ICGI-2000wasthe?fthinaseriesof successfulbiennialinternationalconferencesintheareaofgrammaticalinference. Previous conferences were held in Essex, U.K.; Alicante, Spain; Montpellier, France; and Ames, Iowa, USA. This series of meetings seeks to provide a forum for the presentation and discussion of original research on all aspects of grammatical inference. Gram- tical inference, the process of inferring grammar from given data, is a ?eld that is not only challenging from a purely scienti?c standpoint but also ?nds many applications in real world problems. Despitethefactthatgrammaticalinferenceaddressesproblemsinarelatively narrow area, it uses techniques from many domains, and intersects a number of di?erent disciplines. Researchers in grammatical inference come from ?elds as diverse as machine learning, theoretical computer science, computational ling- stics, pattern recognition and arti?cial neural networks. From a practical standpoint, applications in areas such as natural language acquisition, computational biology, structural pattern recognition, information retrieval, text processing and adaptive intelligent agents have either been - monstrated or proposed in the literature. ICGI-2000 was held jointly with CoNLL-2000, the Computational Natural Language Learning Workshop and LLL-2000, the Second Learning Language in LogicWorkshop.Thetechnicalprogramincludedthepresentationof24accepted papers (out of 35 submitted) as well as joint sessions with CoNLL and LLL. A tutorial program organized by Gabriel Pereira Lopes took place after the meetings and included tutorials by Raymond Mooney, Gregory Grefenstette, Walter Daelemans, Ant´ onio Ribeiro, Joaquim Ferreira da Silva, Gael Dias, Nuno Marques,VitorRossio,Jo˜ aoBalsaandAlexandreAgostini.Thejointrealization of these events represents a unique opportunity for researchers in these related ?elds to interact and exchange ideas.

Specificaties

ISBN13:9783540410119
Taal:Engels
Bindwijze:paperback
Aantal pagina's:316
Uitgever:Springer Berlin Heidelberg
Druk:2000

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Inhoudsopgave

Inference of Finite-State Transducers by Using Regular Grammars and Morphisms.- Computational Complexity of Problems on Probabilistic Grammars and Transducers.- Efficient Ambiguity Detection in C-NFA.- Learning Regular Languages Using Non Deterministic Finite Automata.- Smoothing Probabilistic Automata: An Error-Correcting Approach.- Inferring Subclasses of Contextual Languages.- Permutations and Control Sets for Learning Non-regular Language Families.- On the Complexity of Consistent Identification of Some Classes of Structure Languages.- Computation of Substring Probabilities in Stochastic Grammars.- A Comparative Study of Two Algorithms for Automata Identification.- The Induction of Temporal Grammatical Rules from Multivariate Time Series.- Identification in the Limit with Probability One of Stochastic Deterministic Finite Automata.- Iterated Transductions and Efficient Learning from Positive Data: A Unifying View.- An Inverse Limit of Context-Free Grammars – A New Approach to Identifiability in the Limit.- Synthesizing Context Free Grammars from Sample Strings Based on Inductive CYK Algorithm.- Combination of Estimation Algorithms and Grammatical Inference Techniques to Learn Stochastic Context-Free Grammars.- On the Relationship between Models for Learning in Helpful Environments.- Probabilistic k-Testable Tree Languages.- Learning Context-Free Grammars from Partially Structured Examples.- Identification of Tree Translation Rules from Examples.- Counting Extensional Differences in BC-Learning.- Constructive Learning of Context-Free Languages with a Subpansive Tree.- A Polynomial Time Learning Algorithm of Simple Deterministic Languages via Membership Queries and a Representative Sample.- Improve the Learning of Subsequential Transducers by Using Alignments and Dictionaries.

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        Grammatical Inference: Algorithms and Applications