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005    20230825081447.0
006    m     o  d
007    cr |||||||||||
008    230825s2018    nyua    o     101 0 eng d
035    (CKB)4100000007597602
035    (NjHacI)994100000007597602
035    (Association for Computing Machinery)10.1145/3291801
035    (EXLCZ)994100000007597602
040    NjHacI |beng |erda |cNjHacl
050  4 QA76.9.B45 |b.A876 2018
082 04 005.7 |223
110 2  Association for Computing Machinery, |eauthor, |eissuing body.
245 10 Proceedings of 2018 2nd International Conference on Big Data Research : |bICBDR 2018 : Weihai, China, October 27-29, 2018 / |cAssociation for Computing Machinery ; ACM Digital Library, contributor.
246 30 ICBDR '18
264  1 New York NY : |bACM, |c2018.
300    1 online resource (221 pages) : |billustrations.
336    text |btxt |2rdacontent
337    computer |bc |2rdamedia
338    online resource |bcr |2rdacarrier
490 1  ACM international conference proceedings series
588    Description based on publisher supplied metadata and other sources.
520    Over the past few years big data has emerged a new major pluri-disciplinary research area whose objective is to deal with massive datasets and that are too large to be manipulated by conventional modelling and current computational approaches. As the datasets often available in many disciplines and application areas exponentially grow thanks to the increasing availability of novel sensors and devices, there is nowadays an urgent need to develop novel methods and computational approaches to deal with the high volumes and variety of the large data sources generated in many fields. The range of research challenges still opened are extremely large, from the integration, storage, manipulation, data mining and visualization techniques to the development of computing architectures, cloud and distributed computing platforms to scalable storage systems. Clearly, big data challenges should require multidisciplinary approaches, when different points of view, ideas and experiences should be shared, this favoring exchanges and cross-fertilization on recent trends as well as research directions to consider.
500    Includes index.
650  0 Big data |vCongresses.
650  0 Data mining |vCongresses.
776     |z1-4503-6476-4
710 2  Association for Computing Machinery-Digital Library, |econtributor.
830  0 ACM international conference proceedings series.
906    BOOK