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130605s2013 gw | s |||| 0|eng d |
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|a 9783642388125
|9 978-3-642-38812-5
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|a 10.1007/978-3-642-38812-5
|2 doi
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|2 23
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|a Riguzzi, Fabrizio.
|e editor.
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|a Inductive Logic Programming
|b 22nd International Conference, ILP 2012, Dubrovnik, Croatia, September 17-19, 2012, Revised Selected Papers /
|c edited by Fabrizio Riguzzi, Filip }elezn<U+00fd>.
|h [electronic resource] :
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| 264 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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| 300 |
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|a X, 273 p. 81 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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| 490 |
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|a Lecture Notes in Computer Science,
|v 7842
|x 0302-9743 ;
|
| 505 |
0 |
# |
|a A Relational Approach to Tool-Use Learning in Robots -- A Refinement Operator for Inducing Threaded-Variable Clauses -- Propositionalisation of Continuous Attributes beyond Simple Aggregation -- Topic Models with Relational Features for Drug Design -- Pairwise Markov Logic -- Evaluating Inference Algorithms for the Prolog Factor Language -- Polynomial Time Pattern Matching Algorithm for Ordered Graph Patterns -- Fast Parameter Learning for Markov Logic Networks Using Bayes Nets -- Bounded Least General Generalization -- Itemset-Based Variable Construction in Multi-relational Supervised Learning -- A Declarative Modeling Language for Concept Learning in Description Logics -- Identifying Driver<U+0019>s Cognitive Load Using Inductive Logic Programming -- Opening Doors: An Initial SRL Approach -- Probing the Space of Optimal Markov Logic Networks for Sequence Labeling -- What Kinds of Relational Features Are Useful for Statistical Learning? -- Learning Dishonesty -- Heuristic Inverse Subsumption in Full-Clausal Theories -- Learning Unordered Tree Contraction Patterns in Polynomial TimeA Relational Approach to Tool-Use Learning in Robots -- A Refinement Operator for Inducing Threaded-Variable Clauses -- Propositionalisation of Continuous Attributes beyond Simple Aggregation -- Topic Models with Relational Features for Drug Design -- Pairwise Markov Logic -- Evaluating Inference Algorithms for the Prolog Factor Language -- Polynomial Time Pattern Matching Algorithm for Ordered Graph Patterns -- Fast Parameter Learning for Markov Logic Networks Using Bayes Nets -- Bounded Least General Generalization -- Itemset-Based Variable Construction in Multi-relational Supervised Learning -- A Declarative Modeling Language for Concept Learning in Description Logics -- Identifying Driver<U+0019>s Cognitive Load Using Inductive Logic Programming -- Opening Doors: An Initial SRL Approach -- Probing the Space of Optimal Markov Logic Networks for Sequence Labeling -- What Kinds of Relational Features Are Useful for Statistical Learning?.-Learning Dishonesty.-Heuristic Inverse Subsumption in Full-Clausal Theories.-Learning Unordered Tree Contraction Patterns in Polynomial Time.
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| 520 |
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|a This book constitutes the thoroughly refereed post-proceedings of the 22nd International Conference on Inductive Logic Programming, ILP 2012, held in Dubrovnik, Croatia, in September 2012. The 18 revised full papers were carefully reviewed and selected from 41 submissions. The papers cover the following topics: propositionalization, logical foundations, implementations, probabilistic ILP, applications in robotics and biology, grammatical inference, spatial learning and graph-based learning.
|
| 650 |
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0 |
|a Computer science.
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| 650 |
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0 |
|a Logic design.
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| 650 |
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|a Artificial intelligence.
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| 650 |
1 |
4 |
|a Computer Science.
|
| 650 |
2 |
4 |
|a Mathematical Logic and Formal Languages.
|
| 650 |
2 |
4 |
|a Artificial Intelligence (incl. Robotics).
|
| 650 |
2 |
4 |
|a Programming Techniques.
|
| 650 |
2 |
4 |
|a Logics and Meanings of Programs.
|
| 650 |
2 |
4 |
|a Computation by Abstract Devices.
|
| 650 |
2 |
4 |
|a Computer Science, general.
|
| 700 |
1 |
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|a }elezn<U+00fd>, Filip.
|e editor.
|
| 710 |
2 |
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|a SpringerLink (Online service)
|
| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783642388118
|
| 830 |
# |
0 |
|a Lecture Notes in Computer Science,
|v 7842
|x 0302-9743 ;
|
| 856 |
4 |
0 |
|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-642-38812-5
|
| 912 |
# |
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|a ZDB-2-SCS
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| 912 |
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|a ZDB-2-LNC
|
| 950 |
# |
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|a Computer Science (Springer-11645)
|