LEADER 05527nam 22007095 450 001 996465865503316 005 20200704221041.0 010 $a3-540-70678-X 024 7 $a10.1007/BFb0033338 035 $a(CKB)1000000000234539 035 $a(SSID)ssj0000323583 035 $a(PQKBManifestationID)11259103 035 $a(PQKBTitleCode)TC0000323583 035 $a(PQKBWorkID)10300136 035 $a(PQKB)10492735 035 $a(DE-He213)978-3-540-70678-6 035 $a(PPN)155208934 035 $a(EXLCZ)991000000000234539 100 $a20121227d1996 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aGrammatical Inference: Learning Syntax from Sentences$b[electronic resource] $eThird International Colloquium, ICGI-96, Montpellier, France, September 25 - 27, 1996. Proceedings /$fedited by Laurent Miclet, Colin de la Higuera 205 $a1st ed. 1996. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d1996. 215 $a1 online resource (X, 334 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v1147 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-61778-7 327 $aLearning grammatical structure using statistical decision-trees -- Inductive inference from positive data: from heuristic to characterizing methods -- Unions of identifiable families of languages -- Characteristic sets for polynomial grammatical inference -- Query learning of subsequential transducers -- Lexical categorization: Fitting template grammars by incremental MDL optimization -- Selection criteria for word trigger pairs in language modeling -- Clustering of sequences using a minimum grammar complexity criterion -- A note on grammatical inference of slender context-free languages -- Learning linear grammars from structural information -- Learning of context-sensitive language acceptors through regular inference and constraint induction -- Inducing constraint grammars -- Introducing statistical dependencies and structural constraints in variable-length sequence models -- A disagreement count scheme for inference of constrained Markov networks -- Using knowledge to improve N-Gram language modelling through the MGGI methodology -- Discrete sequence prediction with commented Markov models -- Learning k-piecewise testable languages from positive data -- Learning code regular and code linear languages -- Incremental regular inference -- An incremental interactive algorithm for regular grammar inference -- Inductive logic programming for discrete event systems -- Stochastic simple recurrent neural networks -- Inferring stochastic regular grammars with recurrent neural networks -- Maximum mutual information and conditional maximum likelihood estimations of stochastic regular syntax-directed translation schemes -- Grammatical inference using Tabu Search -- Using domain information during the learning of a subsequential transducer -- Identification of DFA: Data-dependent versus data-independent algorithms. 330 $aThis book constitutes the refereed proceedings of the Third International Colloquium on Grammatical Inference, ICGI-96, held in Montpellier, France, in September 1996. The 25 revised full papers contained in the book together with two invited key papers by Magerman and Knuutila were carefully selected for presentation at the conference. The papers are organized in sections on algebraic methods and algorithms, natural language and pattern recognition, inference and stochastic models, incremental methods and inductive logic programming, and operational issues. 410 0$aLecture Notes in Artificial Intelligence ;$v1147 606 $aArtificial intelligence 606 $aProgramming languages (Electronic computers) 606 $aNatural language processing (Computer science) 606 $aMathematical logic 606 $aPattern recognition 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aProgramming Languages, Compilers, Interpreters$3https://scigraph.springernature.com/ontologies/product-market-codes/I14037 606 $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 615 0$aArtificial intelligence. 615 0$aProgramming languages (Electronic computers). 615 0$aNatural language processing (Computer science). 615 0$aMathematical logic. 615 0$aPattern recognition. 615 14$aArtificial Intelligence. 615 24$aProgramming Languages, Compilers, Interpreters. 615 24$aNatural Language Processing (NLP). 615 24$aMathematical Logic and Formal Languages. 615 24$aPattern Recognition. 676 $a006.3/5 702 $aMiclet$b Laurent$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHiguera$b Colin de la$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aInternational Colloquium on Grammatical Inference$d(3rd :$f1996 :$eMontpellier, France) 906 $aBOOK 912 $a996465865503316 996 $aGrammatical Inference: Learning Syntax from Sentences$92829980 997 $aUNISA