LEADER 03699nam 22004935 450 001 996465318903316 005 20200702024431.0 010 $a3-540-46081-0 024 7 $a10.1007/BFb0017213 035 $a(CKB)1000000000233357 035 $a(SSID)ssj0000324265 035 $a(PQKBManifestationID)11273763 035 $a(PQKBTitleCode)TC0000324265 035 $a(PQKBWorkID)10304221 035 $a(PQKB)11013948 035 $a(DE-He213)978-3-540-46081-7 035 $a(PPN)155217267 035 $a(EXLCZ)991000000000233357 100 $a20121227d1989 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aKnowledge Representation and Organization in Machine Learning$b[electronic resource] /$fedited by Katharina Morik 205 $a1st ed. 1989. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d1989. 215 $a1 online resource (XVIII, 322 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v347 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-50768-X 327 $aExplanation: A source of guidance for knowledge representation -- (Re)presentation issues in second generation expert systems -- Some aspects of learning and reorganization in an analogical representation -- A knowledge-intensive learning system for document retrieval -- Constructing expert systems as building mental models or toward a cognitive ontology for expert systems -- Sloppy modeling -- The central role of explanations in disciple -- An inference engine for representing multiple theories -- The acquisition of model-knowledge for a model-driven machine learning approach -- Using attribute dependencies for rule learning -- Learning disjunctive concepts -- The use of analogy in incremental SBL -- Knowledge base refinement using apprenticeship learning techniques -- Creating high level knowledge structures from simple elements -- Demand-driven concept formation. 330 $aMachine learning has become a rapidly growing field of Artificial Intelligence. Since the First International Workshop on Machine Learning in 1980, the number of scientists working in the field has been increasing steadily. This situation allows for specialization within the field. There are two types of specialization: on subfields or, orthogonal to them, on special subjects of interest. This book follows the thematic orientation. It contains research papers, each of which throws light upon the relation between knowledge representation, knowledge acquisition and machine learning from a different angle. Building up appropriate representations is considered to be the main concern of knowledge acquisition for knowledge-based systems throughout the book. Here machine learning is presented as a tool for building up such representations. But machine learning itself also states new representational problems. This book gives an easy-to-understand insight into a new field with its problems and the solutions it offers. Thus it will be of good use to both experts and newcomers to the subject. 410 0$aLecture Notes in Artificial Intelligence ;$v347 606 $aArtificial intelligence 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aArtificial intelligence. 615 14$aArtificial Intelligence. 676 $a006.3 702 $aMorik$b Katharina$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996465318903316 996 $aKnowledge Representation and Organization in Machine Learning$92831690 997 $aUNISA LEADER 02926nam 2200697 a 450 001 9910783399703321 005 20230617025614.0 010 $a0-19-160848-3 010 $a0-19-160200-0 010 $a1-282-05288-8 010 $a9786612052880 010 $a0-19-153459-5 035 $a(CKB)1000000000024471 035 $a(EBL)3053371 035 $a(OCoLC)922954279 035 $a(SSID)ssj0000087816 035 $a(PQKBManifestationID)11113081 035 $a(PQKBTitleCode)TC0000087816 035 $a(PQKBWorkID)10071588 035 $a(PQKB)11232349 035 $a(StDuBDS)EDZ0000074257 035 $a(MiAaPQ)EBC3053371 035 $a(MiAaPQ)EBC4701235 035 $a(Au-PeEL)EBL3053371 035 $a(CaPaEBR)ebr10288444 035 $a(OCoLC)925415214 035 $a(Au-PeEL)EBL4701235 035 $a(CaONFJC)MIL205288 035 $a(OCoLC)507273408 035 $a(MiAaPQ)EBC7039222 035 $a(Au-PeEL)EBL7039222 035 $a(EXLCZ)991000000000024471 100 $a20041216d2004 fy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 14$aThe judicial construction of Europe$b[electronic resource] /$fAlec Stone Sweet 210 $aOxford ;$aNew York $cOxford University Press$d2004 215 $a1 online resource (294 p.) 300 $aDescription based upon print version of record. 311 $a0-19-927552-1 311 $a0-19-927553-X 320 $aIncludes bibliographical references (p. [245]-264) and indexes. 327 $a""Acknowledgments""; ""Contents""; ""List of Figures""; ""List of Tables""; ""1. The European Court and Integration""; ""2. Constructing a Supranational Constitution""; ""3. The Free Movement of Goods""; ""4. Sex Equality""; ""5. Environmental Protection""; ""6. Conclusion""; ""References""; ""Index of Cases""; ""A""; ""B""; ""C""; ""D""; ""E""; ""F""; ""G""; ""H""; ""I""; ""J""; ""K""; ""L""; ""M""; ""N""; ""O""; ""P""; ""R""; ""S""; ""T""; ""V""; ""W""; ""Index""; ""A""; ""B""; ""C""; ""D""; ""E""; ""F""; ""G""; ""H""; ""I""; ""J""; ""K""; ""L""; ""M""; ""N""; ""O""; ""P""; ""Q""; ""R"" 327 $a""S""""T""; ""U""; ""V""; ""W"" 330 8 $aAfter developing and testing a theory of integration, Alec Stone Sweet assesses the impact of the European Court of Justice on the politics of trade, sex equality, and environmental protection in the European Union. 606 $aConstitutional law$zEuropean Union countries 606 $aPolitical questions and judicial power$zEuropean Union countries 615 0$aConstitutional law 615 0$aPolitical questions and judicial power 676 $a342.24 700 $aStone Sweet$b Alec$0254673 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910783399703321 996 $aThe judicial construction of Europe$93763341 997 $aUNINA