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Data Science de Chengqi Zhang

Data Science: Lecture Notes in Computer Science, cartea 9208

Editat de Chengqi Zhang, Wei Huang, Yong Shi, Philip S. Yu, Yangyong Zhu, Yingjie Tian, Peng Zhang, Jing He
en Limba Engleză Paperback – 12 sep 2015
This book constitutes the refereed proceedings of theSecond International Conference on Data Science, ICDS 2015, held in Sydney,Australia, during August 8-9, 2015.
The 19 revised full papers and 5 short papers presentedwere carefully reviewed and selected from 31 submissions. The papers focus onthe following topics: mathematical issues in data science; big data issues andapplications; data quality and data preparation; data-driven scientificresearch; evaluation and measurement in data service; big data mining andknowledge management; case study of data science; social impacts of datascience.
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Specificații

ISBN-13: 9783319244730
ISBN-10: 3319244736
Pagini: 204
Ilustrații: X, 194 p. 60 illus. in color.
Dimensiuni: 155 x 235 x 12 mm
Greutate: 0.32 kg
Ediția:1st edition 2015
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science

Locul publicării:Cham, Switzerland

Cuprins

Mathematical issues in data science.- Big data issues and applications.- Data quality and data preparation.- Data-driven scientific research.- Evaluation and measurement in data service.- Big data mining and knowledge management.- 
case study of data science.- Social impacts of data science.

Textul de pe ultima copertă

This book constitutes the refereed proceedings of theSecond International Conference on Data Science, ICDS 2015, held in Sydney,Australia, during August 8-9, 2015.
The 19 revised full papers and 5 short papers presentedwere carefully reviewed and selected from 31 submissions. The papers focus onthe following topics: mathematical issues in data science; big data issues andapplications; data quality and data preparation; data-driven scientificresearch; evaluation and measurement in data service; big data mining andknowledge management; case study of data science; social impacts of datascience.