LEADER 04570nam 22007935 450 001 996465754503316 005 20200629230213.0 010 $a3-642-22688-4 024 7 $a10.1007/978-3-642-22688-5 035 $a(CKB)2670000000099856 035 $a(SSID)ssj0000530775 035 $a(PQKBManifestationID)11364235 035 $a(PQKBTitleCode)TC0000530775 035 $a(PQKBWorkID)10570018 035 $a(PQKB)10443483 035 $a(DE-He213)978-3-642-22688-5 035 $a(MiAaPQ)EBC3066996 035 $a(PPN)156309246 035 $a(EXLCZ)992670000000099856 100 $a20110718d2011 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aConceptual Structures for Discovering Knowledge$b[electronic resource] $e19th International Conference on Conceptual Structures, ICCS 2011, Derby, UK, July 25-29, 2011, Proceedings /$fedited by Simon Andrews, Simon Polovina, Richard Hill, Babak Akhgar 205 $a1st ed. 2011. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2011. 215 $a1 online resource (XIV, 424 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v6828 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-642-22687-6 320 $aIncludes bibliographical references and index. 330 $aThis book constitutes the proceedings of the 19th International Conference on Conceptual Structures, ICCS 2011, held in Derby, UK, in July 2011. The 18 full papers and 4 short papers presented together with 12 workshop papers were carefully reviewed and selected for inclusion in the book. The volume also contains 3 invited talks. ICCS focuses on the useful representation and analysis of conceptual knowledge with research and business applications. It advances the theory and practice in connecting the user's conceptual approach to problem solving with the formal structures that computer applications need to bring their productivity to bear. Conceptual structures (CS) represent a family of approaches that builds on the successes of artificial intelligence, business intelligence, computational linguistics, conceptual modelling, information and Web technologies, user modelling, and knowledge management. Two of the workshops contained in this volume cover CS and knowledge discovery in under-traversed domains and in task specific information retrieval. The third addresses CD in learning, teaching and assessment. 410 0$aLecture Notes in Artificial Intelligence ;$v6828 606 $aArtificial intelligence 606 $aDatabase management 606 $aData mining 606 $aMathematical logic 606 $aPattern recognition 606 $aData structures (Computer science) 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 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 $aMathematical Logic and Formal Languages$3https://scigraph.springernature.com/ontologies/product-market-codes/I16048 606 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aData Storage Representation$3https://scigraph.springernature.com/ontologies/product-market-codes/I15025 615 0$aArtificial intelligence. 615 0$aDatabase management. 615 0$aData mining. 615 0$aMathematical logic. 615 0$aPattern recognition. 615 0$aData structures (Computer science). 615 14$aArtificial Intelligence. 615 24$aDatabase Management. 615 24$aData Mining and Knowledge Discovery. 615 24$aMathematical Logic and Formal Languages. 615 24$aPattern Recognition. 615 24$aData Storage Representation. 676 $a006.3 702 $aAndrews$b Simon$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aPolovina$b Simon$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aHill$b Richard$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aAkhgar$b Babak$4edt$4http://id.loc.gov/vocabulary/relators/edt 712 12$aInternational Conference on Conceptual Structures 906 $aBOOK 912 $a996465754503316 996 $aConceptual Structures for Discovering Knowledge$92595061 997 $aUNISA