LEADER 04979nam 22008535 450 001 9910767575603321 005 20251226195902.0 010 $a3-540-78469-1 024 7 $a10.1007/978-3-540-78469-2 035 $a(CKB)1000000000490667 035 $a(SSID)ssj0000318231 035 $a(PQKBManifestationID)11226176 035 $a(PQKBTitleCode)TC0000318231 035 $a(PQKBWorkID)10308176 035 $a(PQKB)11615035 035 $a(DE-He213)978-3-540-78469-2 035 $a(MiAaPQ)EBC3068708 035 $a(PPN)123743796 035 $a(Au-PeEL)EBL3068708 035 $a(CaPaEBR)ebr10533868 035 $a(CaONFJC)MIL134312 035 $a(OCoLC)233973960 035 $a(EXLCZ)991000000000490667 100 $a20100301d2008 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aInductive Logic Programming $e17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers /$fedited by Hendrik Blockeel, Jan Ramon, Jude Shavlik, Prasad Tadepalli 205 $a1st ed. 2008. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2008. 215 $a1 online resource (XI, 307 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v4894 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-540-78468-3 320 $aIncludes bibliographical references and index. 327 $aInvited 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 theForest Through the Trees -- Building Relational World Models for Reinforcement Learning -- An Inductive Learning System for XML Documents. 330 $aThis book contains the post-conference proceedings of the 17th International Conference on Inductive Logic Programming. It covers current topics in inductive logic programming, from theoretical and methodological issues to advanced applications. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v4894 606 $aArtificial intelligence 606 $aSoftware engineering 606 $aComputer programming 606 $aMachine theory 606 $aAlgorithms 606 $aData mining 606 $aArtificial Intelligence 606 $aSoftware Engineering 606 $aProgramming Techniques 606 $aFormal Languages and Automata Theory 606 $aAlgorithms 606 $aData Mining and Knowledge Discovery 615 0$aArtificial intelligence. 615 0$aSoftware engineering. 615 0$aComputer programming. 615 0$aMachine theory. 615 0$aAlgorithms. 615 0$aData mining. 615 14$aArtificial Intelligence. 615 24$aSoftware Engineering. 615 24$aProgramming Techniques. 615 24$aFormal Languages and Automata Theory. 615 24$aAlgorithms. 615 24$aData Mining and Knowledge Discovery. 676 $a005.1/5 701 $aBlockeel$b Hendrik$01759891 712 12$aILP 2007 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910767575603321 996 $aInductive logic programming$94198563 997 $aUNINA