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pro vyhledávání: '"big data analytics frameworks"'
Big data analytics frameworks (BDAFs) have been widely used for data processing applications. These frameworks provide a large number of configuration parameters to users, which leads to a tuning issue that overwhelms users. To address this issue, ma
Externí odkaz:
http://arxiv.org/abs/1808.06008
Akademický článek
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Big data analytics frameworks for the influence of gut microbiota on the development of tic disorder
Publikováno v:
Frontiers in Computational Neuroscience, Vol 16 (2022)
The association between gut microbiota and psychiatric disorders has received increasing research attention. Meanwhile, big data analysis has been utilized in many filed including business, human healthcare analysis, etc. The primary objective of thi
Externí odkaz:
https://doaj.org/article/bd2a9e667ff04b2a954572c0af48830e
Conference
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Autor:
Terence L. van Zyl, David Otoo-Arthur
Publikováno v:
Proceedings of the 2019 2nd International Conference on E-Business, Information Management and Computer Science.
The development of Big Data applications in education has drawn much attention in the last few years due to the enormous benefits it brings to improving teaching and learning. The integration of these Big Data applications in education generates mass
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4a6a709c5ec8839decd4d676c2690904
https://doi.org/10.1145/3377817.3377836
https://doi.org/10.1145/3377817.3377836
Publikováno v:
IEEE BigData
Big data analytics frameworks (BDAFs) have been widely used for data processing applications. These frameworks provide a large number of configuration parameters to users, which leads to a tuning issue that overwhelms users. To address this issue, ma
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::623157935202ee31a4b51a501e8235f1
https://doi.org/10.1109/bigdata.2018.8622018
https://doi.org/10.1109/bigdata.2018.8622018
Publikováno v:
Supercomputing Frontiers ISBN: 9783319699523
SCFA
SCFA
With the rapid development of big data analytics frameworks, many existing high performance computing (HPC) facilities are evolving new capabilities to support big data analytics workloads. However, due to the different workload characteristics and o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7a448a6a8272f573bd423cc25618dfb
https://doi.org/10.1007/978-3-319-69953-0_6
https://doi.org/10.1007/978-3-319-69953-0_6
Publikováno v:
HPCS
To face the increased network traffic in the cloud, data center operators have started adopting an heterogeneous approach in their infrastructures. Heterogeneous infrastructures, e.g. based on FPGAs, can provide higher performance and better energy-e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fb67a4eebf90066c30403f0cdd106db
https://doi.org/10.1109/hpcs.2018.00090
https://doi.org/10.1109/hpcs.2018.00090
Autor:
Vana Kalogeraki, Ioannis Konstantinou, Nikolaos Chalvantzis, Nectarios Koziris, Nikos Zacheilas
Publikováno v:
2018 IEEE International Conference on Autonomic Computing (ICAC)
ICAC
ICAC
In recent years we observe the rapid growth of large-scale analytics applications in a wide range of domains – from healthcare infrastructures to traffic management. The high volume of data that need to be processed has stimulated the development o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a56479607ed0d51076c88a964f19cf8
Conference
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