Situation Recognition Using EventShop
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 computa
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uation Recognition Using EventShop
Situation Recognition Using EventShop
Vivek K. Singh • Ramesh Jain
Situation Recognition Using EventShop
123
Ramesh Jain University of California Irvine, CA, USA
Vivek K. Singh Rutgers University New Brunswick, NJ, USA
ISBN 978-3-319-30535-6 DOI 10.1007/978-3-319-30537-0
ISBN 978-3-319-30537-0 (eBook)
Library of Congress Control Number: 2016936667 © The Author(s) 2016 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG Switzerland
VKS: To my great-grandfather, Shri Parsadi Lal. RJ: To all my research partners.
Preface
Imagine a scenario where millions of aspects of the physical world around us, including weather patterns, stock prices, social phenomena, traffic information, disease incidents, and so on, are accessible to anybody who so desires. Similarly, each individual has access to rich personal data about themselves ranging from their heart rates to movement patterns, to temperature, to gaze, to social interactions, and so on. Such a scenario is not merely science fiction, but rather increasingly becoming a reality for more people than ever before at a pace faster than ever seen before. This marks a significant change in the human thinking about data. In the past, our scientific thinking has often been clouded by the scarcity of data; we collected data only when really needed and the potential insights to be drawn from it were defined even before the data was created. Increasingly we have an abundance of data, i.e., we have more data than what we have the tools and abilities to comprehend and convert into actionable insights. This means that the bottleneck for making significant progress in fields ranging from health to business analysis and to disaster response is no longer the existence of data but rather the tools and techniques to make sense of the data. This book makes a contribu
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