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001 978-3-540-70678-6
003 DE-He213
005 20160624102103.0
007 cr nn 008mamaa
008 121227s1996 gw | s |||| 0|eng d
020 _a9783540706786
_9978-3-540-70678-6
024 7 _a10.1007/BFb0033338
_2doi
050 4 _aQ334-342
050 4 _aTJ210.2-211.495
072 7 _aUYQ
_2bicssc
072 7 _aTJFM1
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
245 1 0 _aGrammatical Interference: Learning Syntax from Sentences
_h[electronic resource] :
_bThird International Colloquium, ICGI-96 Montpellier, France, September 25–27, 1996 Proceedings /
_cedited by Laurent Miclet, Colin Higuera.
260 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c1996.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c1996.
300 _aX, 334 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 Computer Science, Lecture Notes in Artificial Intelligence,
_x0302-9743 ;
_v1147
505 0 _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.
520 _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.
650 0 _aComputer science.
650 0 _aArtificial intelligence.
650 0 _aOptical pattern recognition.
650 1 4 _aComputer Science.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aMathematical Logic and Formal Languages.
650 2 4 _aPattern Recognition.
700 1 _aMiclet, Laurent.
_eeditor.
700 1 _aHiguera, Colin.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783540617785
786 _dSpringer
830 0 _aLecture Notes in Computer Science, Lecture Notes in Artificial Intelligence,
_x0302-9743 ;
_v1147
856 4 0 _uhttp://dx.doi.org/10.1007/BFb0033338
942 _2EBK7454
_cEBK
999 _c36748
_d36748