LEADER 06115nam 22008415 450 001 9910484003603321 005 20251226202153.0 010 $a1-280-38744-0 010 $a9786613565365 010 $a3-642-13840-3 024 7 $a10.1007/978-3-642-13840-9 035 $a(CKB)2670000000028952 035 $a(SSID)ssj0000446534 035 $a(PQKBManifestationID)11327277 035 $a(PQKBTitleCode)TC0000446534 035 $a(PQKBWorkID)10497027 035 $a(PQKB)11710188 035 $a(DE-He213)978-3-642-13840-9 035 $a(MiAaPQ)EBC3065461 035 $a(PPN)149072953 035 $a(BIP)31063982 035 $a(EXLCZ)992670000000028952 100 $a20100701d2010 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aInductive Logic Programming $e19th International Conference, ILP 2009, Leuven, Belgium, July 2-4, 2010, Revised Papers /$fedited by Luc Raedt 205 $a1st ed. 2010. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2010. 215 $a1 online resource (XII, 257 p.) 225 1 $aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v5989 300 $aBibliographic Level Mode of Issuance: Monograph 311 08$a3-642-13839-X 320 $aIncludes bibliographical references and index. 327 $aKnowledge-Directed Theory Revision -- Towards Clausal Discovery for Stream Mining -- On the Relationship between Logical Bayesian Networks and Probabilistic Logic Programming Based on the Distribution Semantics -- Induction of Relational Algebra Expressions -- A Logic-Based Approach to Relation Extraction from Texts -- Discovering Rules by Meta-level Abduction -- Inductive Generalization of Analytically Learned Goal Hierarchies -- Ideal Downward Refinement in the Description Logic -- Nonmonotonic Onto-Relational Learning -- CP-Logic Theory Inference with Contextual Variable Elimination and Comparison to BDD Based Inference Methods -- Speeding Up Inference in Statistical Relational Learning by Clustering Similar Query Literals -- Chess Revision: Acquiring the Rules of Chess Variants through FOL Theory Revision from Examples -- ProGolem: A System Based on Relative Minimal Generalisation -- An Inductive Logic Programming Approach to Validate Hexose Binding Biochemical Knowledge -- Boosting First-Order Clauses for Large, Skewed Data Sets -- Incorporating Linguistic Expertise Using ILP for Named Entity Recognition in Data Hungry Indian Languages -- Transfer Learning via Relational Templates -- Automatic Revision of Metabolic Networks through Logical Analysis of Experimental Data -- Finding Relational Associations in HIV Resistance Mutation Data -- ILP, the Blind, and the Elephant: Euclidean Embedding of Co-proven Queries -- Parameter Screening and Optimisation for ILP Using Designed Experiments -- Don?t Fear Optimality: Sampling for Probabilistic-Logic Sequence Models -- Policy Transfer via Markov Logic Networks -- Can ILP Be Applied to Large Datasets?. 330 $aThe ILP conference series has been the premier forum for work on logic-based approaches to machine learning for almost two decades. The 19th International Conference on Inductive Logic Programming, which was organized in Leuven, July2-4,2009,continuedthistraditionbutalsoreachedouttoothercommunities as it was colocated with SRL-2009 - the International Workshop on Statistical RelationalLearning,andMLG-2009-the7thInternationalWorkshoponMining andLearningwithGraphs. While thesethreeseriesofeventseachhavetheirown focus,emphasis andtradition,they essentiallysharethe problemthatis studied: learning about structured data in the form of graphs, relational descriptions or logic. The colocation of the events was intended to increase the interaction between the three communities. There was a single program with joint invited and tutorial speakers, a panel, regular talks and poster sessions. The invited speakers and tutorial speakers were James Cussens, Jason Eisner, Jure Leskovec, Raymond Mooney, Scott Sanner, and Philip Yu. The panel featured Karsten Borgwardt, Luc De Raedt, Pedro Domingos, Paolo Frasconi, Thomas Gart ¨ ner, Kristian Kersting, Stephen Muggleton, and C. David Page. Video-recordings of these talks can be found atwww. videolectures. net. The overall program featured 30 talks presented in two parallel tracks and 53 posters. The talks and posters were selected on the basis of an extended abstract. These abstracts can be found at http:// dtai. cs. kuleuven. be/ilp-mlg-srl/. Inaddition,asinpreviousyears,a- lectionofthepapersofILP2009havebeenpublishedinavolumeintheLectures Notes in Arti'cial Intelligence seriesandinaspecialissueoftheMachine Lea- ing Journal. 410 0$aLecture Notes in Artificial Intelligence,$x2945-9141 ;$v5989 606 $aMachine theory 606 $aCompilers (Computer programs) 606 $aDatabase management 606 $aInformation storage and retrieval systems 606 $aAlgorithms 606 $aData mining 606 $aFormal Languages and Automata Theory 606 $aCompilers and Interpreters 606 $aDatabase Management 606 $aInformation Storage and Retrieval 606 $aAlgorithms 606 $aData Mining and Knowledge Discovery 615 0$aMachine theory. 615 0$aCompilers (Computer programs). 615 0$aDatabase management. 615 0$aInformation storage and retrieval systems. 615 0$aAlgorithms. 615 0$aData mining. 615 14$aFormal Languages and Automata Theory. 615 24$aCompilers and Interpreters. 615 24$aDatabase Management. 615 24$aInformation Storage and Retrieval. 615 24$aAlgorithms. 615 24$aData Mining and Knowledge Discovery. 676 $a005.1/15 701 $aRaedt$b Luc de$f1964-$01754852 712 12$aILP (Conference) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484003603321 996 $aInductive logic programming$94191363 997 $aUNINA