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R: Mining Spatial, Text, Web, and Social Media Data by Richard Heimann, Nathan Danneman, Pradeepta Mishra, Bater Makhabel

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Chapter 8. Mining Stream, Time-series, and Sequence Data

In this chapter, you will learn how to write mining codes for stream data, time-series data, and sequence data.

The characteristics of stream, time-series, and sequence data are unique, that is, large and endless. It is too large to get an exact result; this means an approximate result will be achieved. The classic data-mining algorithm should be extended, or a new algorithm needs to be designed for this type of the dataset.

In relation to the mining of stream, time-series, and sequence data, there are some topics we can't avoid. They are association, frequent pattern, classification and clustering algorithms, and so on. In the following sections, we will go through these major topics.

In this ...

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