Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Temporal Data Mining

  • Nikos MamoulisEmail author
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_393


Sequence data mining; Temporal association mining; Time series data mining


Temporal data mining refers to the extraction of implicit, nontrivial, and potentially useful abstract information from large collections of temporal data. Temporal data are sequences of a primary data type, most commonly numerical or categorical values, and sometimes multivariate or composite information. Examples of temporal data are regular time series (e.g., stock ticks, EEG), event sequences (e.g., sensor readings, packet traces, medical records, weblog data), and temporal databases (e.g., relations with timestamped tuples, databases with versioning). The common factor of all these sequence types is the total ordering of their elements. They differ on the type of primary information, the regularity of the elements in the sequence, and on whether there is explicit temporal information associated to each element (e.g., timestamps). There are several mining tasks that can be applied on...

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.University of Hong KongHong KongChina

Section editors and affiliations

  • Richard T. Snodgrass
    • 1
  • Christian S. Jensen
    • 2
  1. 1.University of ArizonaTucsonUSA
  2. 2.Aalborg UniversityAalborg ØstDenmark