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Regarding the types of temporal data, I saw on a temporal data mining book (Mitsa, Theophano. Temporal data mining. CRC Press, 2010), that there are 3 types of temporal data: time series, temporal sequences and a semantic temporal data. According to the author:

  • Time-series: ordered real-value measurements at regular time intervals
  • Temporal sequences: timestamped at regular or irregular time intervals

I further explored the difference between the two but is still not clear for me, because from what I could understand time-series is a special case of temporal sequences. Temporal sequences can accept nominal values, symbols, discrete, continuous, or categorical values right? And the data may be collected, as mentioned above, at regular or irregular time intervals. On the other hand, time-series data can only be continuous measurements at regular time intervals, which seems to be a special case of temporal sequences. Am I interpreting wrongly?

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You are correct time-series data are a special case of temporal sequences because time-series data is required to be collected on regular time intervals and constrained to be real-value measurements.

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