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Situation recognition using EventShop

Singh, Vivek K.

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Situation recognition using EventShop

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Situation recognition using EventShop/ by Vivek K. Singh, Ramesh Jain.
作者:	Singh, Vivek K.
其他作者:	Jain, Ramesh.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	xvii, 140 p. :ill. (some col.), digital ;24 cm.
內容註:	Introduction -- Understanding and Using Situations -- Related Work on Situation Recognition -- Overall Framework for Situation Recognition: Overview -- Situation Modeling -- Data Representation and Situation Recognition Operators -- EventShop: System Architecture -- Using EventShop -- Case Studies: Using EventShop for Creating Multiple Situation Recognition Applications -- Research Directions: Challenges and Opportunities.
Contained By:	Springer eBooks
標題:	Pattern recognition systems. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-30537-0
ISBN:	9783319305370

Situation recognition using EventShop
Singh, Vivek K.

Situation recognition using EventShop[electronic resource] /by Vivek K. Singh, Ramesh Jain. - Cham :Springer International Publishing :2016. - xvii, 140 p. :ill. (some col.), digital ;24 cm.

Introduction -- Understanding and Using Situations -- Related Work on Situation Recognition -- Overall Framework for Situation Recognition: Overview -- Situation Modeling -- Data Representation and Situation Recognition Operators -- EventShop: System Architecture -- Using EventShop -- Case Studies: Using EventShop for Creating Multiple Situation Recognition Applications -- Research Directions: Challenges and Opportunities.

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.

ISBN: 9783319305370

Standard No.: 10.1007/978-3-319-30537-0doiSubjects--Topical Terms:

527885
Pattern recognition systems.

LC Class. No.: TK7882.P3

Dewey Class. No.: 006.4

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520 $a 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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