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|a 9783540452652
|9 978-3-540-45265-2
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|a 10.1007/11872436
|2 doi
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|d GrThAP
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|a QA76.7-76.73
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|a QA76.76.C65
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|a COM010000
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|a 005.13
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|a Grammatical Inference: Algorithms and Applications
|h [electronic resource] :
|b 8th International Colloquium, ICGI 2006, Tokyo, Japan, September 20-22, 2006. Proceedings /
|c edited by Yasubumi Sakakibara, Satoshi Kobayashi, Kengo Sato, Tetsuro Nishino, Etsuji Tomita.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2006.
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|a XII, 359 p.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 4201
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|a Invited Papers -- Parsing Without Grammar Rules -- Classification of Biological Sequences with Kernel Methods -- Regular Papers -- Identification in the Limit of Systematic-Noisy Languages -- Ten Open Problems in Grammatical Inference -- Polynomial-Time Identification of an Extension of Very Simple Grammars from Positive Data -- PAC-Learning Unambiguous NTS Languages -- Incremental Learning of Context Free Grammars by Bridging Rule Generation and Search for Semi-optimum Rule Sets -- Variational Bayesian Grammar Induction for Natural Language -- Stochastic Analysis of Lexical and Semantic Enhanced Structural Language Model -- Using Pseudo-stochastic Rational Languages in Probabilistic Grammatical Inference -- Learning Analysis by Reduction from Positive Data -- Inferring Grammars for Mildly Context Sensitive Languages in Polynomial-Time -- Planar Languages and Learnability -- A Unified Algorithm for Extending Classes of Languages Identifiable in the Limit from Positive Data -- Protein Motif Prediction by Grammatical Inference -- Grammatical Inference in Practice: A Case Study in the Biomedical Domain -- Inferring Grammar Rules of Programming Language Dialects -- The Tenjinno Machine Translation Competition -- Large Scale Inference of Deterministic Transductions: Tenjinno Problem 1 -- A Discriminative Model of Stochastic Edit Distance in the Form of a Conditional Transducer -- Learning n-Ary Node Selecting Tree Transducers from Completely Annotated Examples -- Learning Multiplicity Tree Automata -- Learning DFA from Correction and Equivalence Queries -- Using MDL for Grammar Induction -- Characteristic Sets for Inferring the Unions of the Tree Pattern Languages by the Most Fitting Hypotheses -- Learning Deterministic DEC Grammars Is Learning Rational Numbers -- Iso-array Acceptors and Learning -- Poster Papers -- A Merging States Algorithm for Inference of RFSAs -- Query-Based Learning of XPath Expressions -- Learning Finite-State Machines from Inexperienced Teachers -- Suprasymbolic Grammar Induction by Recurrent Self-Organizing Maps -- Graph-Based Structural Data Mining in Cognitive Pattern Interpretation -- Constructing Song Syntax by Automata Induction -- Learning Reversible Languages with Terminal Distinguishability -- Grammatical Inference for Syntax-Based Statistical Machine Translation.
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|a Computer science.
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|a Programming languages (Electronic computers).
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|a Computer logic.
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|a Mathematical logic.
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|a Artificial intelligence.
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|a Computer Science.
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|a Programming Languages, Compilers, Interpreters.
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|a Artificial Intelligence (incl. Robotics).
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|a Mathematical Logic and Formal Languages.
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|a Logics and Meanings of Programs.
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|a Sakakibara, Yasubumi.
|e editor.
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|a Kobayashi, Satoshi.
|e editor.
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|a Sato, Kengo.
|e editor.
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|a Nishino, Tetsuro.
|e editor.
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|a Tomita, Etsuji.
|e editor.
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|a SpringerLink (Online service)
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|t Springer eBooks
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776 |
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|i Printed edition:
|z 9783540452645
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830 |
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|a Lecture Notes in Computer Science,
|x 0302-9743 ;
|v 4201
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|u http://dx.doi.org/10.1007/11872436
|z Full Text via HEAL-Link
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|a ZDB-2-SCS
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|a ZDB-2-LNC
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|a Computer Science (Springer-11645)
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