|
|
|
|
| LEADER |
00000nam a22000005i 4500 |
| 001 |
978-3-540-78469-2 |
| 003 |
DE-He213 |
| 005 |
20221012195700.0 |
| 007 |
cr nn 008mamaa |
| 008 |
100301s2008 gw | s |||| 0|eng d |
| 020 |
|
|
|a 9783540784692
|9 978-3-540-78469-2
|
| 024 |
7 |
|
|a 10.1007/978-3-540-78469-2
|2 doi
|
| 050 |
|
4 |
|a Q334-342
|
| 050 |
|
4 |
|a TA347.A78
|
| 072 |
|
7 |
|a UYQ
|2 bicssc
|
| 072 |
|
7 |
|a COM004000
|2 bisacsh
|
| 072 |
|
7 |
|a UYQ
|2 thema
|
| 082 |
0 |
4 |
|a 006.3
|2 23
|
| 245 |
1 |
0 |
|a Inductive Logic Programming
|h [electronic resource] :
|b 17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers /
|c edited by Hendrik Blockeel, Jan Ramon, Jude Shavlik, Prasad Tadepalli.
|
| 250 |
|
|
|a 1st ed. 2008.
|
| 264 |
|
1 |
|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2008.
|
| 300 |
|
|
|a XI, 307 p.
|b online resource.
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a computer
|b c
|2 rdamedia
|
| 338 |
|
|
|a online resource
|b cr
|2 rdacarrier
|
| 347 |
|
|
|a text file
|b PDF
|2 rda
|
| 490 |
1 |
|
|a Lecture Notes in Artificial Intelligence,
|x 2945-9141 ;
|v 4894
|
| 505 |
0 |
|
|a Invited Talks -- Learning with Kernels and Logical Representations -- Beyond Prediction: Directions for Probabilistic and Relational Learning -- Extended Abstracts -- Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract) -- Learning Directed Probabilistic Logical Models Using Ordering-Search -- Learning to Assign Degrees of Belief in Relational Domains -- Bias/Variance Analysis for Relational Domains -- Full Papers -- Induction of Optimal Semantic Semi-distances for Clausal Knowledge Bases -- Clustering Relational Data Based on Randomized Propositionalization -- Structural Statistical Software Testing with Active Learning in a Graph -- Learning Declarative Bias -- ILP :- Just Trie It -- Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning -- Empirical Comparison of "Hard" and "Soft" Label Propagation for Relational Classification -- A Phase Transition-Based Perspective on Multiple Instance Kernels -- Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates -- Applying Inductive Logic Programming to Process Mining -- A Refinement Operator Based Learning Algorithm for the Description Logic -- Foundations of Refinement Operators for Description Logics -- A Relational Hierarchical Model for Decision-Theoretic Assistance -- Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming -- Revising First-Order Logic Theories from Examples Through Stochastic Local Search -- Using ILP to Construct Features for Information Extraction from Semi-structured Text -- Mode-Directed Inverse Entailment for Full Clausal Theories -- Mining of Frequent Block Preserving Outerplanar Graph Structured Patterns -- Relational Macros for Transfer in Reinforcement Learning -- Seeing the Forest Through the Trees -- Building Relational World Models for Reinforcement Learning -- An Inductive Learning System for XML Documents.
|
| 650 |
|
0 |
|a Artificial intelligence.
|
| 650 |
|
0 |
|a Software engineering.
|
| 650 |
|
0 |
|a Computer programming.
|
| 650 |
|
0 |
|a Machine theory.
|
| 650 |
|
0 |
|a Algorithms.
|
| 650 |
|
0 |
|a Data mining.
|
| 650 |
1 |
4 |
|a Artificial Intelligence.
|
| 650 |
2 |
4 |
|a Software Engineering.
|
| 650 |
2 |
4 |
|a Programming Techniques.
|
| 650 |
2 |
4 |
|a Formal Languages and Automata Theory.
|
| 650 |
2 |
4 |
|a Algorithms.
|
| 650 |
2 |
4 |
|a Data Mining and Knowledge Discovery.
|
| 700 |
1 |
|
|a Blockeel, Hendrik.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
| 700 |
1 |
|
|a Ramon, Jan.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
| 700 |
1 |
|
|a Shavlik, Jude.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
| 700 |
1 |
|
|a Tadepalli, Prasad.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
|
| 710 |
2 |
|
|a SpringerLink (Online service)
|
| 773 |
0 |
|
|t Springer Nature eBook
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9783540847694
|
| 776 |
0 |
8 |
|i Printed edition:
|z 9783540784685
|
| 830 |
|
0 |
|a Lecture Notes in Artificial Intelligence,
|x 2945-9141 ;
|v 4894
|
| 856 |
4 |
0 |
|u https://doi.uam.elogim.com/10.1007/978-3-540-78469-2
|z Texto Completo
|
| 912 |
|
|
|a ZDB-2-SCS
|
| 912 |
|
|
|a ZDB-2-SXCS
|
| 912 |
|
|
|a ZDB-2-LNC
|
| 950 |
|
|
|a Computer Science (SpringerNature-11645)
|
| 950 |
|
|
|a Computer Science (R0) (SpringerNature-43710)
|
