Grammatical Inference: Algorithms and Applications

This book constitutes the refereed proceedings of the 5th International Colloquium on Grammatical Inference, ICGI 2000, held in Lisbon, Portugal in September 2000. The 24 revised full papers presented were carefully reviewed and selected from 35 submissions. The papers address topics like machine learning, automata, theoretical computer science, computational linguistics, pattern recognition, artificial neural networks, natural language acquisition, computational biology, information retrieval, text processing, and adaptive intelligent agents.

Inhalt

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.