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 (u. a.)

ISBN 10: 3030710548 / ISBN 13: 9783030710545

Published by Springer, 2021

About this Item

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 (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xiii | Englisch | 2021 | Springer | EAN 9783030710545 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 119624097

Bibliographic Details

• Title: 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
• Publisher: Springer
• Publication Date: 2021
• Language: English
• ISBN 10: 3030710548
• ISBN 13: 9783030710545
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 14D millimeters 235 millimeters width by 155 millimeters height by 14 millimeters depth
• Weight: 382 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

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 6^th 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.