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Time Series Indexing

You're reading from   Time Series Indexing Implement iSAX in Python to index time series with confidence

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Product type Paperback
Published in Jun 2023
Publisher Packt
ISBN-13 9781838821951
Length 248 pages
Edition 1st Edition
Languages
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Author (1):
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Mihalis Tsoukalos Mihalis Tsoukalos
Author Profile Icon Mihalis Tsoukalos
Mihalis Tsoukalos
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Table of Contents (11) Chapters Close

Preface 1. Chapter 1: An Introduction to Time Series and the Required Python Knowledge 2. Chapter 2: Implementing SAX FREE CHAPTER 3. Chapter 3: iSAX – The Required Theory 4. Chapter 4: iSAX – The Implementation 5. Chapter 5: Joining and Comparing iSAX Indexes 6. Chapter 6: Visualizing iSAX Indexes 7. Chapter 7: Using iSAX to Approximate MPdist 8. Chapter 8: Conclusions and Next Steps 9. Index 10. Other Books You May Enjoy

Background information

In this first section, we are going to learn about the basic definitions and concepts related to iSAX. But first, we are going to mention the research paper that describes the operation of iSAX. iSAX and its operation are described in iSAX: disk-aware mining and indexing of massive time series datasets, which was written by Jin Shieh and Eamonn Keogh. You do not have to read this paper from start to finish but, as we mentioned for the SAX research paper, it would benefit you to read its abstract and introduction section.

Additionally, there have been various improvements to iSAX, mainly to make it faster, which are presented in the following research papers:

  • iSAX 2.0: Indexing and Mining One Billion Time Series, written by Alessandro Camerra, Themis Palpanas, Jin Shieh, and Eamonn Keogh
  • Beyond one billion time series: Indexing and mining very large time series collections with iSAX2+, written by Alessandro Camerra, Jin Shieh, Themis Palpanas, Thanawin...
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