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Big Data in Emergency Management: Exploitation Techniques for Social and Mobile Data (Hardcover, 1st ed. 2020)
Loot Price: R4,259
Discovery Miles 42 590
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Big Data in Emergency Management: Exploitation Techniques for Social and Mobile Data (Hardcover, 1st ed. 2020)
Expected to ship within 12 - 17 working days
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This contributed volume discusses essential topics and the
fundamentals for Big Data Emergency Management and primarily
focusses on the application of Big Data for Emergency Management.
It walks the reader through the state of the art, in different
facets of the big disaster data field. This includes many elements
that are important for these technologies to have real-world
impact. This book brings together different computational
techniques from: machine learning, communication network analysis,
natural language processing, knowledge graphs, data mining, and
information visualization, aiming at methods that are typically
used for processing big emergency data. This book also provides
authoritative insights and highlights valuable lessons by
distinguished authors, who are leaders in this field. Emergencies
are severe, large-scale, non-routine events that disrupt the normal
functioning of a community or a society, causing widespread and
overwhelming losses and impacts. Emergency Management is the
process of planning and taking actions to minimize the social and
physical impact of emergencies and reduces the community's
vulnerability to the consequences of emergencies. Information
exchange before, during and after the disaster periods can greatly
reduce the losses caused by the emergency. This allows people to
make better use of the available resources, such as relief
materials and medical supplies. It also provides a channel through
which reports on casualties and losses in each affected area, can
be delivered expeditiously. Big Data-Driven Emergency Management
refers to applying advanced data collection and analysis
technologies to achieve more effective and responsive
decision-making during emergencies. Researchers, engineers and
computer scientists working in Big Data Emergency Management, who
need to deal with large and complex sets of data will want to
purchase this book. Advanced-level students interested in
data-driven emergency/crisis/disaster management will also want to
purchase this book as a study guide.
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