LEADER 01029nam0-22003131i-450- 001 990003103370403321 005 20070110154936.0 010 $a0-521-08111-4 035 $a000310337 035 $aFED01000310337 035 $a(Aleph)000310337FED01 035 $a000310337 100 $a20030910d1971----km-y0itay50------ba 101 0 $aeng 102 $aGB 200 1 $aInstitutional change and American economic growth$fby Lance E. Davis and Douglass C. North$gwith the assistance of Calla Smorodin 210 $aCambridge$cCambridge University Press$d1971 215 $aVIII, 282 p.$d23 cm 610 0 $aStati Uniti$aIstituzioni e crescita economica 700 1$aDavis,$bLance Edwin$f<1928- >$0118703 701 1$aNorth,$bDouglass Cecil$f<1920- >$0118535 702 1$aSmorodin,$bCalla 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990003103370403321 952 $aF/1.221 DAV$b4051/I$fSES 959 $aSES 996 $aInstitutional change and American economic growth$9461972 997 $aUNINA LEADER 00975nam a2200265 i 4500 001 991002418879707536 005 20020508195909.0 008 931005s1991 it ||| | ita 020 $a8805052582 035 $ab11006420-39ule_inst 035 $aPARLA162236$9ExL 040 $aDip.to Filosofia$bita 100 1 $aPrini, Pietro$0327112 245 13$aIl corpo che siamo :$bintroduzione all'antropologia etica /$cPietro Pietro 260 $aTorino :$bSEI,$c1991 300 $aVI, 186 p. ;$c20 cm. 490 0 $aMorale 650 4$aAntropologia 907 $a.b11006420$b23-02-17$c28-06-02 912 $a991002418879707536 945 $aLE005 Ist.Fil. LIV C 16$g1$i2005000020179$lle005$o-$pE0.00$q-$rl$s- $t0$u1$v3$w1$x0$y.i11123424$z28-06-02 945 $aLE005 MF 36 H 7$g1$i2005000229770$lle005$o-$pE0.00$q-$rl$s- $t0$u1$v0$w1$x0$y.i11123436$z28-06-02 996 $aCorpo che siamo$9861553 997 $aUNISALENTO 998 $ale005$b01-01-93$cm$da $e-$fita$git $h3$i2 LEADER 04846nam 2201225z- 450 001 9910576878103321 005 20220621 035 $a(CKB)5720000000008394 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/84521 035 $a(oapen)doab84521 035 $a(EXLCZ)995720000000008394 100 $a20202206d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aData Science and Knowledge Discovery 210 $aBasel$cMDPI - Multidisciplinary Digital Publishing Institute$d2022 215 $a1 online resource (254 p.) 311 08$a3-0365-4316-3 311 08$a3-0365-4315-5 330 $aData Science (DS) is gaining significant importance in the decision process due to a mix of various areas, including Computer Science, Machine Learning, Math and Statistics, domain/business knowledge, software development, and traditional research. In the business field, DS's application allows using scientific methods, processes, algorithms, and systems to extract knowledge and insights from structured and unstructured data to support the decision process. After collecting the data, it is crucial to discover the knowledge. In this step, Knowledge Discovery (KD) tasks are used to create knowledge from structured and unstructured sources (e.g., text, data, and images). The output needs to be in a readable and interpretable format. It must represent knowledge in a manner that facilitates inferencing. KD is applied in several areas, such as education, health, accounting, energy, and public administration. This book includes fourteen excellent articles which discuss this trending topic and present innovative solutions to show the importance of Data Science and Knowledge Discovery to researchers, managers, industry, society, and other communities. The chapters address several topics like Data mining, Deep Learning, Data Visualization and Analytics, Semantic data, Geospatial and Spatio-Temporal Data, Data Augmentation and Text Mining. 606 $aComputer science$2bicssc 606 $aInformation technology industries$2bicssc 610 $aactivity recognition 610 $aadaptation process 610 $aArcGIS 610 $aartificial intelligence 610 $aattribution 610 $aauthorship 610 $aautomation 610 $abig data 610 $aBig Data 610 $abox-counting framework 610 $achatbots 610 $aclassification 610 $acontent base image retrieval 610 $aCOVID-19 610 $acrisis reporting 610 $acustomer relationship management (CRM) 610 $adashboard 610 $adata analysis 610 $adata analytics 610 $adata augmentation 610 $adata mining 610 $adata science 610 $adatabases 610 $adecision systems 610 $adeep features 610 $adeep learning 610 $adigital humanities 610 $adigital infrastructures 610 $adistracted driving 610 $adriving behavior 610 $adriving operation area 610 $ae-commerce 610 $aeconomic determinants of open data 610 $aESP32 microcontroller 610 $afeature extraction 610 $aforensic intelligence 610 $afractal dimension 610 $ageoinformation technology 610 $agovernance and social institutions 610 $ahumanities 610 $aICT 610 $ainformation systems 610 $ainterdisciplinary research 610 $ainternet of things 610 $aioCOVID19 610 $ajournalists 610 $alinked open data 610 $aLoRaWAN 610 $amachine learning 610 $amedia analytics 610 $amedia criticism 610 $amultimedia document retrieval 610 $an/a 610 $aneural networks 610 $anews media 610 $aopen government data 610 $aprediction by partial matching 610 $apublic health 610 $arough sets 610 $arule based systems 610 $aSARS-CoV-2 610 $ascript Python 610 $asemantic information retrieval 610 $asmart homes 610 $asocial sciences 610 $aspatio-temporal 610 $aterritorial road network 610 $atext mining 610 $atextbook research 610 $aThe Things Network 610 $aWeb Intelligence 610 $aWebGIS 615 7$aComputer science 615 7$aInformation technology industries 700 $aPortela$b Filipe$4edt$01268012 702 $aPortela$b Filipe$4oth 906 $aBOOK 912 $a9910576878103321 996 $aData Science and Knowledge Discovery$93021749 997 $aUNINA