Situation Recognition Using EventShop de Vivek K. Singh

Situation Recognition Using EventShop

Vivek K. Singh

Ramesh Jain

en Limba Engleză Paperback – 30 mai 2018

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.

Citește tot Restrânge

Cuprins

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.

Caracteristici

Explains the practical implementation of EventShop, an open-source software platform Maximizes reader insight into the concept of situation recognition, i.e. deriving actionable insights from heterogeneous, real-time, big multimedia data to benefit human lives and resources in different applications Describes a framework for converting multitudes of data streams (including weather patterns, stock prices, social phenomena, traffic information, and disease incidents) into actionable insights Includes supplementary material: sn.pub/extras