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Titlebook: New Trends in Databases and Information Systems; ADBIS 2016 Short Pap Mirjana Ivanovi?,Bernhard Thalheim,Pietro Michiard Conference proceed

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書目名稱New Trends in Databases and Information Systems
副標(biāo)題ADBIS 2016 Short Pap
編輯Mirjana Ivanovi?,Bernhard Thalheim,Pietro Michiard
視頻videohttp://file.papertrans.cn/666/665921/665921.mp4
概述Includes supplementary material:
叢書名稱Communications in Computer and Information Science
圖書封面Titlebook: New Trends in Databases and Information Systems; ADBIS 2016 Short Pap Mirjana Ivanovi?,Bernhard Thalheim,Pietro Michiard Conference proceed
描述.This book constitutes the thoroughly refereed short papers, workshops and Doctoral Consortium papers of the 20th East European Conference on Advances in Databases and Information Systems, ADBIS 2016, held in Prague, Czech Republic, in August 2016...The 11 short papers and one historical paper were carefully selected and reviewed from 85 submissions. The rest of papers was selected from reviewing processes of 2 workshops and Doctoral Consortium. The papers are organized in topical sections on ADBIS Short Papers, Third International Workshop on Big Data Applications and Principles (BigDap 2016), Second International Workshop on Data Centered Smart Applications (DCSA 2016) and ADBIS Doctoral Consortium..
出版日期Conference proceedings 2016
關(guān)鍵詞algorithms; big data; data management systems; data mining; database systems; information integration; inf
版次1
doihttps://doi.org/10.1007/978-3-319-44066-8
isbn_softcover978-3-319-44065-1
isbn_ebook978-3-319-44066-8Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer International Publishing Switzerland 2016
The information of publication is updating

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Canonical Data Model for Data Warehousenical model to support materialized integration of data during data warehouse creation. The considered data warehouse is based on the concept of grid file. To extract data from several sources, to create the materialized view, and to effectively organize queries on the multidimensional data a comput
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Towards Spatial Crowdsourcing in Vehicular Networks Using Mobile Agentscal advances in these fields but also to meet the increasing demand of “connected” applications and services. Although vehicular networks have not been fully developed yet, they could be used in a near future as a means to provide a number of interesting applications and services that need the excha
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