000 03978nam a22005895i 4500
001 978-3-540-45257-7
003 DE-He213
005 20240423132536.0
007 cr nn 008mamaa
008 121227s2000 gw | s |||| 0|eng d
020 _a9783540452577
_9978-3-540-45257-7
024 7 _a10.1007/b75249
_2doi
050 4 _aQA76.76.C65
072 7 _aUMC
_2bicssc
072 7 _aCOM010000
_2bisacsh
072 7 _aUMC
_2thema
082 0 4 _a005.45
_223
245 1 0 _aGrammatical Inference: Algorithms and Applications
_h[electronic resource] :
_b5th International Colloquium, ICGI 2000, Lisbon, Portugal, September 11-13, 2000 Proceedings /
_cedited by Arlindo L. Oliveira.
250 _a1st ed. 2000.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2000.
300 _aVIII, 316 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v1891
505 0 _aInference 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 andDictionaries.
650 0 _aCompilers (Computer programs).
650 0 _aPattern recognition systems.
650 0 _aArtificial intelligence.
650 0 _aMachine theory.
650 0 _aAlgorithms.
650 1 4 _aCompilers and Interpreters.
650 2 4 _aAutomated Pattern Recognition.
650 2 4 _aArtificial Intelligence.
650 2 4 _aFormal Languages and Automata Theory.
650 2 4 _aAlgorithms.
700 1 _aOliveira, Arlindo L.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540410119
776 0 8 _iPrinted edition:
_z9783662197219
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v1891
856 4 0 _uhttps://doi.org/10.1007/b75249
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
912 _aZDB-2-BAE
942 _cSPRINGER
999 _c188927
_d188927