01021nam0 22002651i 450 UON0021144520231205103336.84104-359-8936-720030730d1994 |0itac50 baengGB|||| |||||ˆA ‰ small gathering of bonesPatricia PowellOxfordHeinemann1994. 137 p. ; 20 cm.001UON001736252001 Caribbean writers Series210 LondonHeinemann.GBOxfordUONL000029813Narrativa americana in inglese21POWELLPatriciaUONV127366682893HeinemannUONV247100650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00211445SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI AME VI c 2.73 0201 SI LO 63628 5 0201 BuonoSmall gathering of bones1262190UNIOR00966nam0 22002651i 450 UON0005723220231205102251.62720020107d1910 |0itac50 baaraDZ|||| 1||||Banat Su'adKa'b Ben ZuhayrRené BassetAlgerPip. A. Jourdan1910176 p.22 cmDZAlgerUONL005716ARA VI BBYPAESI ARABI - LETTERATURA CLASSICA - CRITICA - POESIAAKA'B BEN ZUHAIRUONV030769650376BassetRenéUONV014473*Adolphe *JourdanUONV249584650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00057232SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI ARA VI BBY 059 SI MR 35034 7 059 Banat Su'ad1149627UNIOR03397nam 2200865z- 450 991059507920332120230220(CKB)5680000000080733(oapen)https://directory.doabooks.org/handle/20.500.12854/92131(oapen)doab97461(EXLCZ)99568000000008073320202209d2022 |y 0engurmn|---annantxtrdacontentcrdamediacrrdacarrierGeo Data Science for TourismBaselMDPI - Multidisciplinary Digital Publishing Institute20221 online resource (188 p.)3-0365-5029-1 3-0365-5030-5 This reprint describes the recent challenges in tourism seen from the point of view of data science. Thanks to the use of the most popular Data Science concepts, you can easily recognise trends and patterns in tourism, detect the impact of tourism on the environment, and predict future trends in tourism. This reprint starts by describing how to analyse data related to the past, then it moves on to detecting behaviours in the present, and, finally, it describes some techniques to predict future trends. By the end of the reprint, you will be able to use data science to help tourism businesses make better use of data and improve their decision making and operations..GeographybicsscResearch & information: generalbicsscA-level scenic spotsAGNES clusteringattraction imageBayesian STVC modelcellular signaling dataChinaChinese regional tourismcommunitiescorporate social responsibilityembeddingGeodetectorgeographic detectorgeographical data modeling analysisgreen hotelgreen hotel certificationheterogeneous information networkinfluencing factorsmajor tourist citiesnetwork connectionnode centralityobstacle factorsonline tourism reviewsrelatedness between attractionssocial network analysissocioeconomic and environmental driversspace-time deductionspatial distributionspatiotemporal estimation mappingspatiotemporal evolutionspatiotemporal influencing factorsspatiotemporal nonstationary regressionsports tourismtopic extractiontour route searchingtourism economic vulnerabilitytourism flowtourist attraction clusteringtourist attraction reachability space modeltrend analysistrend predictionGeographyResearch & information: generalMarchetti Andreaedt127673Lo Duca AngelicaedtMarchetti AndreaothLo Duca AngelicaothBOOK9910595079203321Geo Data Science for Tourism3035014UNINA