ACM Books
eBook - ePub

ACM Books

  1. 162 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

ACM Books

Book details
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About This Book

This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data. The first phase is the data-driven process of hypothesis formation, requiring the analysis of large amounts of data to find strong candidate hypotheses. The second phase is hypothesis testing, wherein a domain expert's knowledge and judgment is used to test and modify the candidate hypotheses.

The book is intended as a primer on Event Mining for data-enthusiasts and information professionals interested in employing these event-based data analysis techniques in diverse applications. The reader is introduced to frameworks for temporal knowledge representation and reasoning, as well as temporal data mining and pattern discovery. Also discussed are the design principles of event mining systems. The approach is reified by the presentation of an event mining system called EventMiner, a computational framework for building explanatory models. The book contains case studies of using EventMiner in asthma risk management and an architecture for the objective self. The text can be used by researchers interested in harnessing the value of heterogeneous big data for designing explanatory event-based models in diverse application areas such as healthcare, biological data analytics, predictive maintenance of systems, computer networks, and business intelligence.

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Information

Publisher
ACM Books
Year
2021
ISBN
9781450384841
Topic
Computer Science
Subtopic
System Administration
Index
Computer Science

Table of contents

  1. Cover
  2. Halftitle
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Preface
  7. Chapter 1 Introduction
  8. Chapter 2 Think Events: From Signals to Events
  9. Chapter 3 Event Mining and Pattern Discovery
  10. Chapter 4 Design Principles of Event Mining Systems
  11. Chapter 5 Event Mining Applications
  12. Chapter 6 EventMiner Framework
  13. Chapter 7 Conclusion and Future Direction
  14. Bibliography
  15. Authors’ Biographies
  16. Index