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Situation Recognition Using EventShop (Hardcover, 1st ed. 2016)
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Situation Recognition Using EventShop (Hardcover, 1st ed. 2016)
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This book presents a framework for converting multitudes of data
streams available today including weather patterns, stock prices,
social media, traffic information, and disease incidents into
actionable insights based on situation recognition. It
computationally defines the notion of situations as an abstraction
of millions of data points into actionable insights, describes a
computational framework to model and evaluate such situations and
presents an open-source web-based system called EventShop to
implement them without necessitating programming expertise. The
book is useful for both practitioners and researchers working in
the field of situation-aware computing. It acts as a primer for
data-enthusiasts and information professionals interested in
harnessing the value of heterogeneous big data for building diverse
situation-based applications. It also can be used as a reference
text by researchers working in areas as varied as database design,
multimodel concept recognition, and middle-ware and ubiquitous
computing to design and develop frameworks that allow users to
create their own situation recognition frameworks.
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