LEADER 04681nam 22006495 450 001 9910767586303321 005 20200703062007.0 010 $a3-540-69583-4 024 7 $a10.1007/3-540-63494-0 035 $a(CKB)1000000000234718 035 $a(SSID)ssj0000323943 035 $a(PQKBManifestationID)11282864 035 $a(PQKBTitleCode)TC0000323943 035 $a(PQKBWorkID)10304249 035 $a(PQKB)11630093 035 $a(DE-He213)978-3-540-69583-7 035 $a(PPN)155227718 035 $a(EXLCZ)991000000000234718 100 $a20121227d1997 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aInductive Logic Programming$b[electronic resource] $e6th International Workshop, ILP-96, Stockholm, Sweden, August 26-28, 1996, Selected Papers /$fedited by Stephen Muggleton 205 $a1st ed. 1997. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d1997. 215 $a1 online resource (X, 402 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v1314 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-63494-0 327 $aInductive logic programming for natural language processing -- An initial experiment into stereochemistry-based drug design using inductive logic programming -- Applying ILP to diterpene structure elucidation from 13C NMR spectra -- Analysis and prediction of piano performances using inductive logic programming -- Noise detection and elimination applied to noise handling in a KRK chess endgame -- Feature construction with inductive logic programming: A study of quantitative predictions of biological activity by structural attributes -- Polynomial-time learning in logic programming and constraint logic programming -- Analyzing and learning ECG waveforms -- Learning rules that classify ocular fundus images for glaucoma diagnosis -- A new design and implementation of progol by bottom-up computation -- Inductive logic program synthesis with DIALOGS -- Relational knowledge discovery in databases -- Efficient ?-subsumption based on graph algorithms -- Integrity constraints in ILP using a Monte Carlo approach -- Restructuring chain datalog programs -- Top-down induction of logic programs from incomplete samples -- Least generalizations under implication -- Efficient proof encoding -- Learning Logic programs with random classification noise -- Handling Quantifiers in ILP -- Learning from positive data -- ?-Subsumption and its application to learning from positive-only examples. 330 $aThis book constitutes the strictly refereed post-workshop proceedings of the 6th International Workshop on Inductive Logic Programming, ILP-96, held in Stockholm, Sweden, in August 1996. The 21 full papers were carefully reviewed and selected for inclusion in the book in revised version. Also included is the invited contribution "Inductive logic programming for natural language processing" by Raymond J. Mooney. Among the topics covered are natural language learning, drug design, NMR and ECG analysis, glaucoma diagnosis, efficiency measures for implementations and database interaction, program synthesis, proof encoding and learning in the absence of negative data, and least generalizations under implication ordering. 410 0$aLecture Notes in Artificial Intelligence ;$v1314 606 $aArchitecture, Computer 606 $aSoftware engineering 606 $aArtificial intelligence 606 $aComputer programming 606 $aComputer System Implementation$3https://scigraph.springernature.com/ontologies/product-market-codes/I13057 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$3https://scigraph.springernature.com/ontologies/product-market-codes/I14010 615 0$aArchitecture, Computer. 615 0$aSoftware engineering. 615 0$aArtificial intelligence. 615 0$aComputer programming. 615 14$aComputer System Implementation. 615 24$aSoftware Engineering/Programming and Operating Systems. 615 24$aArtificial Intelligence. 615 24$aProgramming Techniques. 676 $a005.1/15 702 $aMuggleton$b Stephen$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aILP (Conference) 906 $aBOOK 912 $a9910767586303321 996 $aInductive Logic Programming$92804417 997 $aUNINA