LEADER 06296nam 22007455 450 001 996465394303316 005 20200629231423.0 010 $a3-540-30109-7 024 7 $a10.1007/b10011 035 $a(CKB)1000000000212524 035 $a(DE-He213)978-3-540-30109-7 035 $a(SSID)ssj0000178506 035 $a(PQKBManifestationID)11156317 035 $a(PQKBTitleCode)TC0000178506 035 $a(PQKBWorkID)10240310 035 $a(PQKB)11290154 035 $a(MiAaPQ)EBC3088537 035 $a(PPN)155176307 035 $a(EXLCZ)991000000000212524 100 $a20121227d2004 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aInductive Logic Programming$b[electronic resource] $e14th International Conference, ILP 2004, Porto, Portugal, September 6-8, 2004, Proceedings /$fedited by Rui Camacho, Ross King, Ashwin Srinivasan 205 $a1st ed. 2004. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2004. 215 $a1 online resource (IX, 358 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v3194 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-22941-8 320 $aIncludes bibliographical references and index. 327 $aInvited Papers -- Automated Synthesis of Data Analysis Programs: Learning in Logic -- At the Interface of Inductive Logic Programming and Statistics -- From Promising to Profitable Applications of ILP: A Case Study in Drug Discovery -- Systems Biology: A New Challenge for ILP -- Scaling Up ILP: Experiences with Extracting Relations from Biomedical Text -- Research Papers -- Macro-Operators Revisited in Inductive Logic Programming -- Bottom-Up ILP Using Large Refinement Steps -- On the Effect of Caching in Recursive Theory Learning -- FOIL-D: Efficiently Scaling FOIL for Multi-relational Data Mining of Large Datasets -- Learning an Approximation to Inductive Logic Programming Clause Evaluation -- Learning Ensembles of First-Order Clauses for Recall-Precision Curves: A Case Study in Biomedical Information Extraction -- Automatic Induction of First-Order Logic Descriptors Type Domains from Observations -- On Avoiding Redundancy in Inductive Logic Programming -- Generalization Algorithms for Second-Order Terms -- Circumscription Policies for Induction -- Logical Markov Decision Programs and the Convergence of Logical TD(?) -- Learning Goal Hierarchies from Structured Observations and Expert Annotations -- Efficient Evaluation of Candidate Hypotheses in -log -- An Efficient Algorithm for Reducing Clauses Based on Constraint Satisfaction Techniques -- Improving Rule Evaluation Using Multitask Learning -- Learning Logic Programs with Annotated Disjunctions -- A Simulated Annealing Framework for ILP -- Modelling Inhibition in Metabolic Pathways Through Abduction and Induction -- First Order Random Forests with Complex Aggregates -- A Monte Carlo Study of Randomised Restarted Search in ILP -- Addendum -- Learning, Logic, and Probability: A Unified View. 330 $a?How often we recall, with regret?, wrote Mark Twain about editors, ?that Napoleon once shot at a magazine editor and missed him and killed a publisher. But we remember with charity, that his intentions were good. ? Fortunately, we live in more forgiving times, and are openly able to express our pleasure at being the editors of this volume containing the papers selected for presentation at the 14th International Conference on Inductive Logic Programming. ILP 2004 was held in Porto from the 6th to the 8th of September, under the auspices of the Department of Electrical Engineering and Computing of the Faculty of Engineering of the University of Porto (FEUP), and the Laboratī orio de Intelig? encia Arti?cial e Ci? encias da Computaļ c? ao (LIACC). This annual me- ing of ILP practitioners and curious outsiders is intended to act as the premier forum for presenting the most recent and exciting work in the ?eld. Six invited talks?three from ?elds outside ILP, but nevertheless highly relevant to it? and 20 full presentations formed the nucleus of the conference. It is the full-length papersofthese20presentationsthatcomprisethebulkofthisvolume. Asisnow common with the ILP conference, presentations made to a ?Work-in-Progress? track will, hopefully, be available elsewhere. We gratefully acknowledge the continued support of Kluwer Academic P- lishers for the ?Best Student Paper? award on behalf of the Machine Lea- ing journal; and Springer-Verlag for continuing to publish the proceedings of these conferences. 410 0$aLecture Notes in Artificial Intelligence ;$v3194 606 $aSoftware engineering 606 $aArtificial intelligence 606 $aComputer programming 606 $aMathematical logic 606 $aSoftware Engineering/Programming and Operating Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I14002 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aProgramming Techniques$3https://scigraph.springernature.com/ontologies/product-market-codes/I14010 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 615 0$aSoftware engineering. 615 0$aArtificial intelligence. 615 0$aComputer programming. 615 0$aMathematical logic. 615 14$aSoftware Engineering/Programming and Operating Systems. 615 24$aArtificial Intelligence. 615 24$aProgramming Techniques. 615 24$aMathematical Logic and Formal Languages. 676 $a005.115 686 $a007.64$2NDC9 702 $aCamacho$b Rui$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKing$b Ross$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSrinivasan$b Ashwin$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aILP (Conference) 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465394303316 996 $aInductive Logic Programming$9772244 997 $aUNISA