2
$\begingroup$

In the context of time series data mining, I have read about time series segmentation and time series clustering, but I couldn't differentiate between both. In case they are different, how these methods are correlated with each other?

Well from my understanding (please correct me if I am wrong), the segmentation is considered as a preprocessing step for the clustering phase. I mean that the segmentation step is used mainly to partition your time series data into segments, let's say into states. After that, a conventional clustering algorithm can be applied to group these segments into clusters (similar segments belong to the same cluster).

As an example, let's say that the segmentation process represents a given time series into the following segments: (S1, S2, S3, S4, S5, S6). Then after applying the segmentation process, a conventional clustering method is applied to cluster the extracted segments. So we might end up with something like this: If k = 3: then K1 {S1, S5}, K2 {S3, S6}, K3 {S2, S4}

Please correct me if I am mistaken, and provide links for more clarification if you have any.

$\endgroup$
2
$\begingroup$

Actually there is no fixed terminology and these two terms sometimes used in the same meaning and sometimes different. I would suggest following the terminology bellow for yourself, then you can differentiate methods according to this:

  • Time-Series Segmentation means partitioning an individual time series to similar segments i.e. clustering within an individual time-series (e.g. i have a video in which someone is reading a book for a while, then starts walking and then starts cycling. now I want to segment these three actions).

Suggestion: State-Space reconstruction, moving Autocorrelation, moving DTW, Fourier Analysis, Visibility Graphs or any other method which can measure the similarity of a time-series with itself.

  • Time-Series Clustering (or this) means finding similar time-series within a dataset of time-series (e.g. i have 10 brain signals, 5 from healthy subjects 5 from patients without knowing who is patient and who is healthy. Now I want to cluster this dataset into two clusters)

Suggestion: Build a similarity matrix between time-series using e.g. DTW and then apply Spectral Clustering (just improvised. If you search literature there should be more mature solutions)

Hope it helped :)

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.