Heterogeneous data management, polystores, and analytics for healthcare : VLDB Workshops, Poly 2020 and DMAH 2020, virtual event, August 31 and September 4, 2020, Revised selected papers / Vijay Gadepally, Timothy Mattson, Michael Stonebraker, Tim Kraska, Fusheng Wang, Gang Luo, Jun Kong, Alevtina Dubovitskaya (eds.).

This book constitutes revised selected papers from two VLDB workshops: The International Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, Poly 2020, and the 6th International Workshop on Data Management and Analytics for Medicine and He...

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Bibliographic Details
Main Authors: Gadepally, Vijay (Author), Mattson, Timothy G., 1958- (Author), Stonebraker, Michael (Author), Kraska, Tim (Author), Wang, Fusheng (Assistant professor) (Author), Luo, Gang (Assistant professor) (Author), Kong, Jun, 1978- (Author), Dubovitskaya, Alevtina (Author)
Corporate Authors: Poly (Workshop) Online), DMAH (Workshop), International Conference on Very Large Data Bases
Format: Ebook
Language:English
Published: Cham : Springer, 2021.
Series:Lecture notes in computer science ; 12633.
LNCS sublibrary. Security and cryptology.
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Online Access:Springer eBooks
Description
Summary:This book constitutes revised selected papers from two VLDB workshops: The International Workshop on Polystore Systems for Heterogeneous Data in Multiple Databases with Privacy and Security Assurances, Poly 2020, and the 6th International Workshop on Data Management and Analytics for Medicine and Healthcare, DMAH 2020, which were held virtually on August 31 and September 4, 2020. For Poly 2020, 4 full and 3 short papers were accepted from 10 submissions; and for DMAH 2020, 7 full and 2 short papers were accepted from a total of 15 submissions. The papers were organized in topical sections as follows: Privacy, Security and/or Policy Issues for Heterogenous Data; COVID-19 Data Analytics and Visualization; Deep Learning based Biomedical Data Analytics; NLP based Learning from Unstructured Data; Biomedical Data Modelling and Prediction.
Item Description:Includes author index.
Physical Description:1 online resource (235 pages).
ISBN:3030710548
9783030710545
3030710556
9783030710552
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