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Fundamentals of Big Data Network Analysis for Research and Industry (Hardcover)
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Fundamentals of Big Data Network Analysis for Research and Industry (Hardcover)
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Fundamentals of Big Data Network Analysis for Research and Industry
Hyunjoung Lee, Institute of Green Technology, Yonsei University,
Republic of Korea Il Sohn, Material Science and Engineering, Yonsei
University, Republic of Korea Presents the methodology of big data
analysis using examples from research and industry There are large
amounts of data everywhere, and the ability to pick out crucial
information is increasingly important. Contrary to popular belief,
not all information is useful; big data network analysis assumes
that data is not only large, but also meaningful, and this book
focuses on the fundamental techniques required to extract essential
information from vast datasets. Featuring case studies drawn
largely from the iron and steel industries, this book offers
practical guidance which will enable readers to easily understand
big data network analysis. Particular attention is paid to the
methodology of network analysis, offering information on the method
of data collection, on research design and analysis, and on the
interpretation of results. A variety of programs including UCINET,
NetMiner, R, NodeXL, and Gephi for network analysis are covered in
detail. Fundamentals of Big Data Network Analysis for Research and
Industry looks at big data from a fresh perspective, and provides a
new approach to data analysis. This book : Explains the basic
concepts in understanding big data and filtering meaningful data
Presents big data analysis within the networking perspective
Features methodology applicable to research and industry Describes
in detail the social relationship between big data and its
implications Provides insight into identifying patterns and
relationships between seemingly unrelated big data Fundamentals of
Big Data Network Analysis for Research and Industry will prove a
valuable resource for analysts, research engineers, industrial
engineers, marketing professionals, and any individuals dealing
with accumulated large data whose interest is to analyze and
identify potential relationships among data sets.
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