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020 _a9783540487517
_9978-3-540-48751-7
024 7 _a10.1007/3-540-48751-4
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aInductive Logic Programming
_h[electronic resource] :
_b9th International Workshop, ILP-99, Bled, Slovenia, June 24-27, 1999, Proceedings /
_cedited by Saso Dzeroski, Peter A. Flach.
250 _a1st ed. 1999.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c1999.
300 _aVIII, 312 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 ;
_v1634
505 0 _aI Invited Papers -- Probabilistic Relational Models -- Inductive Databases -- Some Elements of Machine Learning -- II Contributed Papers -- Refinement Operators Can Be (Weakly) Perfect -- Combining Divide-and-Conquer and Separate-and-Conquer for Efficient and Effective Rule Induction -- Refining Complete Hypotheses in ILP -- Acquiring Graphic Design Knowledge with Nonmonotonic Inductive Learning -- Morphosyntactic Tagging of Slovene Using Progol -- Experiments in Predicting Biodegradability -- 1BC: A First-Order Bayesian Classifier -- Sorted Downward Refinement: Building Background Knowledge into a Refinement Operator for Inductive Logic Programming -- A Strong Complete Schema for Inductive Functional Logic Programming -- Application of Different Learning Methods to Hungarian Part-of-Speech Tagging -- Combining LAPIS and WordNet for the Learning of LR Parsers with Optimal Semantic Constraints -- Learning Word Segmentation Rules for Tag Prediction -- Approximate ILP Rules by Backpropagation Neural Network: A Result on Thai Character Recognition -- Rule Evaluation Measures: A Unifying View -- Improving Part of Speech Disambiguation Rules by Adding Linguistic Knowledge -- On Sufficient Conditions for Learnability of Logic Programs from Positive Data -- A Bounded Search Space of Clausal Theories -- Discovering New Knowledge from Graph Data Using Inductive Logic Programming -- Analogical Prediction -- Generalizing Refinement Operators to Learn Prenex Conjunctive Normal Forms -- Theory Recovery -- Instance based function learning -- Some Properties of Inverse Resolution in Normal Logic Programs -- An Assessment of ILP-assisted models for toxicology and the PTE-3 experiment.
650 0 _aArtificial intelligence.
650 0 _aSoftware engineering.
650 0 _aComputer programming.
650 1 4 _aArtificial Intelligence.
650 2 4 _aSoftware Engineering.
650 2 4 _aProgramming Techniques.
700 1 _aDzeroski, Saso.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aFlach, Peter A.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783540661092
776 0 8 _iPrinted edition:
_z9783662186336
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v1634
856 4 0 _uhttps://doi.org/10.1007/3-540-48751-4
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912 _aZDB-2-SXCS
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