Big Scientific Data Management: First International Conference, BigSDM 2018, Beijing, China, November 30 – December 1, 2018, Revised Selected Papers: Lecture Notes in Computer Science, cartea 11473
Editat de Jianhui Li, Xiaofeng Meng, Ying Zhang, Wenjuan Cui, Zhihui Duen Limba Engleză Paperback – 7 aug 2019
The 24 full papers presented together with 7 short papers were carefully reviewed and selected from 86 submissions. The topics involved application cases in the big scientific data management, paradigms for enhancing scientific discovery through big data, data management challenges posed by big scientific data, machine learning methods to facilitate scientific discovery, science platforms and storage systems for large scale scientific applications, data cleansing and quality assurance of science data, and data policies.
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Specificații
ISBN-13: 9783030280604
ISBN-10: 3030280608
Pagini: 332
Ilustrații: XIII, 332 p. 172 illus., 113 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.49 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Information Systems and Applications, incl. Internet/Web, and HCI
Locul publicării:Cham, Switzerland
ISBN-10: 3030280608
Pagini: 332
Ilustrații: XIII, 332 p. 172 illus., 113 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.49 kg
Ediția:1st ed. 2019
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Information Systems and Applications, incl. Internet/Web, and HCI
Locul publicării:Cham, Switzerland
Cuprins
Application cases in the big scientific data management.- Paradigms for enhancing scientific discovery through big data.- Data management challenges posed by big scientific data.- Machine learning methods to facilitate scientific discovery.- Science platforms and storage systems for large scale scientific applications.- Data cleansing and quality assurance of science data.- Data policies.