LEADER 05597nam 22007575 450 001 9910483197403321 005 20251226203346.0 024 7 $a10.1007/11536314 035 $a(CKB)1000000000213169 035 $a(SSID)ssj0000318229 035 $a(PQKBManifestationID)11266627 035 $a(PQKBTitleCode)TC0000318229 035 $a(PQKBWorkID)10307959 035 $a(PQKB)11301281 035 $a(DE-He213)978-3-540-31851-4 035 $a(MiAaPQ)EBC3067577 035 $a(PPN)123096596 035 $a(EXLCZ)991000000000213169 100 $a20100721d2005 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aInductive Logic Programming $e15th International Conference, ILP 2005, Bonn, Germany, August 10-13, 2005, Proceedings /$fedited by Stefan Kramer, Bernhard Pfahringer 205 $a1st ed. 2005. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2005. 215 $a1 online resource (XIV, 434 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3625 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$aPrinted edition: 9783540281771 320 $aIncludes bibliographical references and index. 327 $aResearch Papers -- An Output-Polynomial Time Algorithm for Mining Frequent Closed Attribute Trees -- Guiding Inference Through Relational Reinforcement Learning -- Converting Semantic Meta-knowledge into Inductive Bias -- Learning Teleoreactive Logic Programs from Problem Solving -- A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment -- Distance Based Generalisation -- Automatic Induction of Abduction and Abstraction Theories from Observations -- Logical Bayesian Networks and Their Relation to Other Probabilistic Logical Models -- Strategies to Parallelize ILP Systems -- Inducing Causal Laws by Regular Inference -- Online Closure-Based Learning of Relational Theories -- Learning Closed Sets of Labeled Graphs for Chemical Applications -- ILP Meets Knowledge Engineering: A Case Study -- Spatial Clustering of Structured Objects -- Generalization Behaviour of Alkemic Decision Trees -- Predicate Selection for Structural Decision Trees -- Induction of the Indirect Effects of Actions by Monotonic Methods -- Probabilistic First-Order Theory Revision from Examples -- Inductive Equivalence of Logic Programs -- Deriving a Stationary Dynamic Bayesian Network from a Logic Program with Recursive Loops -- A Study of Applying Dimensionality Reduction to Restrict the Size of a Hypothesis Space -- Polynomial Time Inductive Inference of TTSP Graph Languages from Positive Data -- Classifying Relational Data with Neural Networks -- Efficient Sampling in Relational Feature Spaces -- Invited Papers -- Why Computers Need to Learn About Music -- Tutorial on Statistical Relational Learning -- Machine Learning for Systems Biology -- Five Problems in Five Areas for Five Years. 330 $a1 ?Change is inevitable.? Embracing this quote we have tried to carefully exp- iment with the format of this conference, the 15th International Conference on Inductive Logic Programming, hopefully making it even better than it already was. But it will be up to you, the inquisitive reader of this book, to judge our success. The major changes comprised broadening the scope of the conference to include more diverse forms of non-propositional learning, to once again have tutorials on exciting new areas, and, for the ?rst time, to also have a discovery challenge as a platform for collaborative work. This year the conference was co-located with ICML 2005, the 22nd Inter- tional Conference on Machine Learning, and also in close proximity to IJCAI 2005, the 19th International Joint Conference on Arti?cial Intelligence. - location can be tricky, but we greatly bene?ted from the local support provided by Codrina Lauth, Michael May, and others. We were also able to invite all ILP and ICML participants to shared events including a poster session, an invited talk, and a tutorial about the exciting new area of ?statistical relational lea- ing?. Two more invited talks were exclusively given to ILP participants and were presented as a kind of stock-taking??ttingly so for the 15th event in a series?but also tried to provide a recipe for future endeavours. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v3625 606 $aSoftware engineering 606 $aArtificial intelligence 606 $aComputer programming 606 $aMachine theory 606 $aAlgorithms 606 $aSoftware Engineering 606 $aArtificial Intelligence 606 $aProgramming Techniques 606 $aFormal Languages and Automata Theory 606 $aAlgorithms 615 0$aSoftware engineering. 615 0$aArtificial intelligence. 615 0$aComputer programming. 615 0$aMachine theory. 615 0$aAlgorithms. 615 14$aSoftware Engineering. 615 24$aArtificial Intelligence. 615 24$aProgramming Techniques. 615 24$aFormal Languages and Automata Theory. 615 24$aAlgorithms. 676 $a005.1/15 701 $aKramer$b Stefan$cProf. Dr.$0894236 701 $aPfahringer$b Bernhard$01758420 712 12$aILP (Conference) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483197403321 996 $aInductive logic programming$94196618 997 $aUNINA