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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 II
BuchKartoniert, Paperback
587 Seiten
Englisch
Springererschienen am16.09.20171st ed. 2017
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, 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.mehr
Verfügbare Formate
BuchKartoniert, Paperback
EUR53,49
BuchKartoniert, Paperback
EUR106,99
E-BookPDF1 - PDF WatermarkE-Book
EUR53,49

Produkt

KlappentextThis 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, 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.
Details
ISBN/GTIN978-981-10-6387-9
ProduktartBuch
EinbandartKartoniert, Paperback
Verlag
Erscheinungsjahr2017
Erscheinungsdatum16.09.2017
Auflage1st ed. 2017
ReiheCommunications in Computer and Information Science
Seiten587 Seiten
SpracheEnglisch
Gewicht920 g
IllustrationenXXVI, 587 p. 272 illus.
Artikel-Nr.43715464

Inhalt/Kritik

Inhaltsverzeichnis
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.mehr

Schlagworte