Data Science | 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018, Zhengzhou, China, September 21-23, 2018, Proceedings, Part II

Qinglei Zhou (u. a.)

ISBN 10: 9811322058 / ISBN 13: 9789811322051

Published by Springer, 2018

About this Item

Data Science | 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018, Zhengzhou, China, September 21-23, 2018, Proceedings, Part II | Qinglei Zhou (u. a.) | Taschenbuch | xxix | Englisch | 2018 | Springer | EAN 9789811322051 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Seller Inventory # 114094639

Bibliographic Details

• Title: Data Science | 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018, Zhengzhou, China, September 21-23, 2018, Proceedings, Part II
• Publisher: Springer
• Publication Date: 2018
• Language: English
• ISBN 10: 9811322058
• ISBN 13: 9789811322051
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 37D millimeters 235 millimeters width by 155 millimeters height by 37 millimeters depth
• Weight: 1013 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

This two volume set (CCIS 901 and 902) constitutes the refereed proceedings of the 4th International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2018 (originally ICYCSEE) held in Zhengzhou, China, in September 2018. 

The 125 revised full papers presented in these two volumes were carefully reviewed and selected from 1057 submissions. The papers cover a wide range of topics related to basic theory and techniques for data science including mathematical issues in data science, computational theory for data science, big data management and applications, data quality and data preparation, evaluation and measurement in data science, data visualization, big data mining and knowledge management, infrastructure for data science, machine learning for data science, data security and privacy, applications of data science, case study of data science, multimedia data management and analysis, data-driven scientific research, data-driven bioinformatics, data-driven healthcare, data-driven management, data-driven eGovernment, data-driven smart city/planet, data marketing and economics, social media and recommendation systems, data-driven security, data-driven business model innovation, social and/or organizational impacts of data science.