LEADER 04588nam 22008295 450 001 9910484000703321 005 20200909224115.0 010 $a3-319-23525-7 024 7 $a10.1007/978-3-319-23525-7 035 $a(CKB)3890000000001388 035 $a(SSID)ssj0001558582 035 $a(PQKBManifestationID)16183647 035 $a(PQKBTitleCode)TC0001558582 035 $a(PQKBWorkID)14818534 035 $a(PQKB)10799742 035 $a(DE-He213)978-3-319-23525-7 035 $a(MiAaPQ)EBC5594969 035 $a(PPN)188460896 035 $a(EXLCZ)993890000000001388 100 $a20150828d2015 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aMachine Learning and Knowledge Discovery in Databases $eEuropean Conference, ECML PKDD 2015, Porto, Portugal, September 7-11, 2015, Proceedings, Part II /$fedited by Annalisa Appice, Pedro Pereira Rodrigues, Vítor Santos Costa, João Gama, Alípio Jorge, Carlos Soares 205 $a1st ed. 2015. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015. 215 $a1 online resource (XLII, 773 p. 198 illus.) 225 1 $aLecture Notes in Artificial Intelligence ;$v9285 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-319-23524-9 330 $aThe three volume set LNAI 9284, 9285, and 9286 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2015, held in Porto, Portugal, in September 2015. The 131 papers presented in these proceedings were carefully reviewed and selected from a total of 483 submissions. These include 89 research papers, 11 industrial papers, 14 nectar papers, 17 demo papers. They were organized in topical sections named: classification, regression and supervised learning; clustering and unsupervised learning; data preprocessing; data streams and online learning; deep learning; distance and metric learning; large scale learning and big data; matrix and tensor analysis; pattern and sequence mining; preference learning and label ranking; probabilistic, statistical, and graphical approaches; rich data; and social and graphs. Part III is structured in industrial track, nectar track, and demo track. 410 0$aLecture Notes in Artificial Intelligence ;$v9285 606 $aData mining 606 $aArtificial intelligence 606 $aPattern recognition 606 $aInformation storage and retrieval 606 $aDatabase management 606 $aApplication software 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 $aPattern Recognition$3https://scigraph.springernature.com/ontologies/product-market-codes/I2203X 606 $aInformation Storage and Retrieval$3https://scigraph.springernature.com/ontologies/product-market-codes/I18032 606 $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024 606 $aInformation Systems Applications (incl. Internet)$3https://scigraph.springernature.com/ontologies/product-market-codes/I18040 615 0$aData mining. 615 0$aArtificial intelligence. 615 0$aPattern recognition. 615 0$aInformation storage and retrieval. 615 0$aDatabase management. 615 0$aApplication software. 615 14$aData Mining and Knowledge Discovery. 615 24$aArtificial Intelligence. 615 24$aPattern Recognition. 615 24$aInformation Storage and Retrieval. 615 24$aDatabase Management. 615 24$aInformation Systems Applications (incl. Internet). 676 $a006.312 702 $aAppice$b Annalisa$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aRodrigues$b Pedro Pereira$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSantos Costa$b Vítor$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aGama$b João$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aJorge$b Alípio$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSoares$b Carlos$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484000703321 996 $aMachine Learning and Knowledge Discovery in Databases$93568347 997 $aUNINA