LEADER 05386nam 22007935 450 001 996466245703316 005 20200705110733.0 010 $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(EXLCZ)991000000000490667 100 $a20100301d2008 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aInductive Logic Programming$b[electronic resource] $e17th International Conference, ILP 2007, Corvallis, OR, USA, June 19-21, 2007, Revised Selected Papers /$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 $aLecture Notes in Artificial Intelligence ;$v4894 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-78468-3 320 $aIncludes bibliographical references and index. 327 $aInvited Talks -- Learning with Kernels and Logical Representations -- Beyond Prediction: Directions for Probabilistic and Relational Learning -- Extended Abstracts -- Learning Probabilistic Logic Models from Probabilistic Examples (Extended Abstract) -- Learning Directed Probabilistic Logical Models Using Ordering-Search -- Learning to Assign Degrees of Belief in Relational Domains -- Bias/Variance Analysis for Relational Domains -- Full Papers -- Induction of Optimal Semantic Semi-distances for Clausal Knowledge Bases -- Clustering Relational Data Based on Randomized Propositionalization -- Structural Statistical Software Testing with Active Learning in a Graph -- Learning Declarative Bias -- ILP :- Just Trie It -- Learning Relational Options for Inductive Transfer in Relational Reinforcement Learning -- Empirical Comparison of ?Hard? and ?Soft? Label Propagation for Relational Classification -- A Phase Transition-Based Perspective on Multiple Instance Kernels -- Combining Clauses with Various Precisions and Recalls to Produce Accurate Probabilistic Estimates -- Applying Inductive Logic Programming to Process Mining -- A Refinement Operator Based Learning Algorithm for the Description Logic -- Foundations of Refinement Operators for Description Logics -- A Relational Hierarchical Model for Decision-Theoretic Assistance -- Using Bayesian Networks to Direct Stochastic Search in Inductive Logic Programming -- Revising First-Order Logic Theories from Examples Through Stochastic Local Search -- Using ILP to Construct Features for Information Extraction from Semi-structured Text -- Mode-Directed Inverse Entailment for Full Clausal Theories -- Mining of Frequent Block Preserving Outerplanar Graph Structured Patterns -- Relational Macros for Transfer in Reinforcement Learning -- Seeing the Forest Through the Trees -- Building Relational World Models for Reinforcement Learning -- An Inductive Learning System for XML Documents. 410 0$aLecture Notes in Artificial Intelligence ;$v4894 606 $aArtificial intelligence 606 $aSoftware engineering 606 $aComputer programming 606 $aMathematical logic 606 $aAlgorithms 606 $aData mining 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aSoftware Engineering/Programming and Operating Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I14002 606 $aProgramming Techniques$3https://scigraph.springernature.com/ontologies/product-market-codes/I14010 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 615 0$aArtificial intelligence. 615 0$aSoftware engineering. 615 0$aComputer programming. 615 0$aMathematical logic. 615 0$aAlgorithms. 615 0$aData mining. 615 14$aArtificial Intelligence. 615 24$aSoftware Engineering/Programming and Operating Systems. 615 24$aProgramming Techniques. 615 24$aMathematical Logic and Formal Languages. 615 24$aAlgorithm Analysis and Problem Complexity. 615 24$aData Mining and Knowledge Discovery. 676 $a005.1/5 702 $aBlockeel$b Hendrik$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRamon$b Jan$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aShavlik$b Jude$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTadepalli$b Prasad$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aILP 2007 906 $aBOOK 912 $a996466245703316 996 $aInductive Logic Programming$9772244 997 $aUNISA