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International Conference of Pioneering Computer Scientists, Engineers and Educators (2017 :)

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Data science = third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017, Changsha, China, September 22-24, 2017 : proceedings.. Part I /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data science/ edited by Beiji Zou ... [et al.].
Reminder of title:	third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017, Changsha, China, September 22-24, 2017 : proceedings.
remainder title:	ICPCSEE 2017
other author:	Zou, Beiji.
corporate name:	International Conference of Pioneering Computer Scientists, Engineers and Educators
Published:	Singapore :Springer Singapore : : 2017.,
Description:	xxv, 769 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Data mining - Congresses. -
Online resource:	http://dx.doi.org/10.1007/978-981-10-6385-5
ISBN:	9789811063855

Data science = third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017, Changsha, China, September 22-24, 2017 : proceedings.. Part I /
Data sciencethird International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017, Changsha, China, September 22-24, 2017 : proceedings.Part I /[electronic resource] :ICPCSEE 2017edited by Beiji Zou ... [et al.]. - Singapore :Springer Singapore :2017. - xxv, 769 p. :ill., digital ;24 cm. - Communications in computer and information science,7271865-0929 ;. - Communications in computer and information science ;727..

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.

This two volume set (CCIS 727 and 728) constitutes the refereed proceedings of the Third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017 (originally ICYCSEE) held in Changsha, China, in September 2017. The 112 revised full papers presented in these two volumes were carefully reviewed and selected from 987 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, D ata-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.

ISBN: 9789811063855

Standard No.: 10.1007/978-981-10-6385-5doiSubjects--Topical Terms:

551626
Data mining
--Congresses.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Data science = third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017, Changsha, China, September 22-24, 2017 : proceedings.. Part I /
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520 $a This two volume set (CCIS 727 and 728) constitutes the refereed proceedings of the Third International Conference of Pioneering Computer Scientists, Engineers and Educators, ICPCSEE 2017 (originally ICYCSEE) held in Changsha, China, in September 2017. The 112 revised full papers presented in these two volumes were carefully reviewed and selected from 987 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, D ata-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.
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