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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

What is an index and why do we need indexing?

Can you imagine searching for a surname in an unsorted list of names? Can you imagine looking for a book in a library that does not sort its books based on book subject (the Dewey system) and then book title and author surname? I cannot! Both examples showcase a naïve but efficient indexing scheme. The more complex the data, the more sophisticated the index should be in order to perform quick searches and maybe updates on the data.

Figure 1.2 shows the visualization of a really small iSAX index – in reality, as a time series can be really huge, iSAX indexes tend to be much bigger and more complex.

Figure 1.2 – A small iSAX index

Figure 1.2 – A small iSAX index

Do not try to understand the iSAX index or the titles of the nodes at this point. Everything is going to become clearer in Chapter 2 and Chapter 3. For now, keep in mind that the titles of the nodes are SAX words and that there exist two kinds of nodes on an iSAX...

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