
Data Science
7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021, Taiyuan, China, September 17-20, 2021, Proceedings, Part I
Springer (Publisher)
Published on 11. September 2021
Book
Paperback/Softback
XXII, 545 pages
978-981-16-5939-3 (ISBN)
Description
This two volume set (CCIS 1451 and 1452) constitutes the refereed proceedings of the 7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021 held in Taiyuan, China, in September 2021.
The 81 papers presented in these two volumes were carefully reviewed and selected from 256 submissions. The papers are organized in topical sections on big data management and applications; social media and recommendation systems; infrastructure for data science; basic theory and techniques for data science; machine learning for data science; multimedia data management and analysis; social media and recommendation systems; data security and privacy; applications of data science; education research, methods and materials for data science and engineering; research demo.
More details
Series
Edition
1st ed. 2021
Language
English
Place of publication
Singapore
Singapore
Target group
Professional and scholarly
Illustrations
107 s/w Abbildungen, 159 farbige Abbildungen
XXII, 545 p. 266 illus., 159 illus. in color.
Dimensions
Height: 235 mm
Width: 155 mm
Thickness: 31 mm
Weight
855 gr
ISBN-13
978-981-16-5939-3 (9789811659393)
DOI
10.1007/978-981-16-5940-9
Schweitzer Classification
Other editions
Additional editions

Jianchao Zeng | Pinle Qin | Weipeng Jing
Data Science
7th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2021, Taiyuan, China, September 17-20, 2021, Proceedings, Part I
E-Book
09/2021
Springer
€117.69
Available for download
Content
Big Data Management and Applications.- Social Media and Recommendation Systems.- Infrastructure for Data Science.- Basic Theory and Techniques for Data Science.- Machine Learning for Data Science.- Multimedia Data Management and Analysis.