Book Image

Time Series Indexing

By : Mihalis Tsoukalos
Book Image

Time Series Indexing

By: Mihalis Tsoukalos

Overview of this book

Time series are everywhere, ranging from financial data and system metrics to weather stations and medical records. Being able to access, search, and compare time series data quickly is essential, and this comprehensive guide enables you to do just that by helping you explore SAX representation and the most effective time series index, iSAX. The book begins by teaching you about the implementation of SAX representation in Python as well as the iSAX index, along with the required theory sourced from academic research papers. The chapters are filled with figures and plots to help you follow the presented topics and understand key concepts easily. But what makes this book really great is that it contains the right amount of knowledge about time series indexing using the right amount of theory and practice so that you can work with time series and develop time series indexes successfully. Additionally, the presented code can be easily ported to any other modern programming language, such as Swift, Java, C, C++, Ruby, Kotlin, Go, Rust, and JavaScript. By the end of this book, you'll have learned how to harness the power of iSAX and SAX representation to efficiently index and analyze time series data and will be equipped to develop your own time series indexes and effectively work with time series data.
Table of Contents (11 chapters)

iSAX – The Required Theory

Now that we know all about SAX, including normalization and computing the SAX representation of a subsequence, it is time to learn the theory behind the iSAX index, which, at the time of writing, is considered one of the best time-series indexes. Improved versions of iSAX that make iSAX faster and more compact exist, but the core ideas remain the same.

As you might have guessed from its name, iSAX depends on SAX in some way. Put simply, the keys to every iSAX index are SAX representations. Therefore, searching in an iSAX index depends on SAX representations.

At this point, I believe it would be good to provide more information about iSAX to help you while reading this chapter. An iSAX index is a tree-like structure where the root, and only the root, can have multiple children, and all the children of the root are binary trees underneath. Additionally, to create an iSAX index, we need a time series and a threshold value, which is the maximum number...