LEADER 04525nam 22006735 450 001 996466326303316 005 20200630013631.0 010 $a3-030-00338-8 024 7 $a10.1007/978-3-030-00338-8 035 $a(CKB)4100000006674999 035 $a(DE-He213)978-3-030-00338-8 035 $a(MiAaPQ)EBC6312512 035 $a(PPN)230538606 035 $a(EXLCZ)994100000006674999 100 $a20180829d2018 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aReasoning Web. Learning, Uncertainty, Streaming, and Scalability$b[electronic resource] $e14th International Summer School 2018, Esch-sur-Alzette, Luxembourg, September 22?26, 2018, Tutorial Lectures /$fedited by Claudia d?Amato, Martin Theobald 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (XI, 237 p. 47 illus.) 225 1 $aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v11078 311 $a3-030-00337-X 327 $aPractical Normative Reasoning with Defeasible Deontic Logic -- Efficient SPARQL Queries on Very Large Knowledge Graphs -- A Tutorial on Query Answering and Reasoning over Probabilistic Knowledge Bases -- Cold-start Knowledge Base Population using Ontology-based Information Extraction with Conditional Random Fields -- Machine Learning with and for Knowledge Graphs -- Rule Induction and Reasoning over Knowledge Graphs -- Storing and Querying Semantic Data in the Cloud -- Engineering of Web Stream Processing Applications -- Reasoning at Scale. . 330 $aThe research areas of Semantic Web, Linked Data, and Knowledge Graphs have recently received a lot of attention in academia and industry. Since its inception in 2001, the Semantic Web has aimed at enriching the existing Web with meta-data and processing methods, so as to provide Web-based systems with intelligent capabilities such as context awareness and decision support. The Semantic Web vision has been driving many community efforts which have invested a lot of resources in developing vocabularies and ontologies for annotating their resources semantically. Besides ontologies, rules have long been a central part of the Semantic Web framework and are available as one of its fundamental representation tools, with logic serving as a unifying foundation. Linked Data is a related research area which studies how one can make RDF data available on the Web and interconnect it with other data with the aim of increasing its value for everybody. Knowledge Graphs have been shown useful not only for Web search (as demonstrated by Google, Bing, etc.) but also in many application domains. 410 0$aInformation Systems and Applications, incl. Internet/Web, and HCI ;$v11078 606 $aDatabase management 606 $aData mining 606 $aArtificial intelligence 606 $aApplication software 606 $aMathematical logic 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aData Mining and Knowledge Discovery$3https://scigraph.springernature.com/ontologies/product-market-codes/I18030 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 606 $aComputer Appl. in Administrative Data Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/I2301X 606 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 615 0$aDatabase management. 615 0$aData mining. 615 0$aArtificial intelligence. 615 0$aApplication software. 615 0$aMathematical logic. 615 14$aDatabase Management. 615 24$aData Mining and Knowledge Discovery. 615 24$aArtificial Intelligence. 615 24$aComputer Appl. in Administrative Data Processing. 615 24$aMathematical Logic and Formal Languages. 676 $a025.04 702 $ad?Amato$b Claudia$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTheobald$b Martin$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466326303316 996 $aReasoning Web. Learning, Uncertainty, Streaming, and Scalability$92262502 997 $aUNISA