LEADER 01854nam 2200589 450 001 9910460263303321 005 20200903223051.0 010 $a1-78441-587-1 035 $a(CKB)3710000000341149 035 $a(OCoLC)905548746 035 $a(CaPaEBR)ebrary11008330 035 $a(SSID)ssj0001431940 035 $a(PQKBManifestationID)11778887 035 $a(PQKBTitleCode)TC0001431940 035 $a(PQKBWorkID)11384589 035 $a(PQKB)11458332 035 $a(MiAaPQ)EBC1922164 035 $a(Au-PeEL)EBL1922164 035 $a(CaPaEBR)ebr11008330 035 $a(CaONFJC)MIL695255 035 $a(OCoLC)900606181 035 $a(EXLCZ)993710000000341149 100 $a20150131h20152015 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt 182 $cc 183 $acr 200 00$aAdvances in accounting education $eteaching and curriculum innovations /$fedited by Timothy J. Rupert 205 $aFirst edition. 210 1$aBingley, England :$cEmerald,$d2015. 210 4$d©2015 215 $a1 online resource (180 p.) 225 0 $aAdvances in Accounting Education: Teaching and Curriculum Innovations,$x1085-4622 ;$vVolume 16 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a1-322-63973-6 311 $a1-78441-588-X 320 $aIncludes bibliographical references at the end of each chapters. 606 $aAccounting$xStudy and teaching 606 $aEducational innovations 608 $aElectronic books. 615 0$aAccounting$xStudy and teaching. 615 0$aEducational innovations. 676 $a657.071 702 $aRupert$b Timothy J. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910460263303321 996 $aAdvances in accounting education$91893481 997 $aUNINA LEADER 03551nam 22008415 450 001 9910743387103321 005 20260319100302.0 010 $a981-16-9708-6 010 $a981-16-9709-4 010 $a981-16-9709-4 024 7 $a10.1007/978-981-16-9709-8 035 $a(CKB)5100000000193934 035 $a(MiAaPQ)EBC6858300 035 $a(Au-PeEL)EBL6858300 035 $a(DE-He213)978-981-16-9709-8 035 $a(PPN)262174138 035 $a(EXLCZ)995100000000193934 100 $a20220114d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aBig Data $e9th CCF Conference, BigData 2021, Guangzhou, China, January 8?10, 2022, Revised Selected Papers /$fedited by Xiangke Liao, Wei Zhao, Enhong Chen, Nong Xiao, Li Wang, Yang Gao, Yinghuan Shi, Changdong Wang, Dan Huang 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (334 pages) 225 1 $aCommunications in Computer and Information Science,$x1865-0937 ;$v1496 311 08$a981-16-9708-6 327 $aBig Data Analysis and Applications -- Big Data and Deep Learning -- Big Data Intelligent Algorithms -- Big Data Privacy and Security -- Image and Natural Language Big Data. 330 $aThis book constitutes the proceedings of the 9th CCF Conference on Big Data, BigData 2021, held in Guangzhou, China, in January 2022. Due to the COVID-19 pandemic BigData 2021 was postponed to 2022. The 21 full papers presented in this volume were carefully reviewed and selected from 66 submissions. They present recent research on theoretical and technical aspects on big data, as well as on digital economy demands in big data applications. . 410 0$aCommunications in Computer and Information Science,$x1865-0937 ;$v1496 606 $aArtificial intelligence 606 $aComputer engineering 606 $aComputer networks 606 $aEducation$xData processing 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aData structures (Computer science) 606 $aInformation theory 606 $aArtificial Intelligence 606 $aComputer Engineering and Networks 606 $aComputer Engineering and Networks 606 $aComputers and Education 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aData Structures and Information Theory 606 $aDades massives$2thub 608 $aCongressos$2thub 608 $aLlibres electrònics$2thub 615 0$aArtificial intelligence. 615 0$aComputer engineering. 615 0$aComputer networks. 615 0$aEducation$xData processing. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aData structures (Computer science) 615 0$aInformation theory. 615 14$aArtificial Intelligence. 615 24$aComputer Engineering and Networks. 615 24$aComputer Engineering and Networks. 615 24$aComputers and Education. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aData Structures and Information Theory. 615 7$aDades massives 676 $a006.3 702 $aLiao$b Xiangke 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910743387103321 996 $aBig Data$91412830 997 $aUNINA