Temporal Data Outlier Detection Task
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A Temporal Data Outlier Detection Task is a sequential data outlier detection task that is a temporal analysis task (for temporal data).
- Context:
- It can range from being a Discrete-Time Outlier Detection Task to being a Continuous-Time Outlier Detection Task.
- It can range from (typically) being a Within-a-Temporal Sequence Outlier Detection Task to being a Entire-Temporal Sequence Outlier Detection Task.
- It can be solved by a Temporal Data Outlier Detection System (that implements a Temporal Data Outlier Detection Algorithm).
- ...
- Example(s):
- Counter-Example(s):
- See: Spatial Outlier Detection.
References
2014
- (Gupta et al., 2014a) ⇒ Madhu Gupta, Jing Gao, Charu C Aggarwal, and Jiawei Han. (2014). “Outlier Detection for Temporal Data: A Survey.” In: Knowledge and Data Engineering, IEEE Transactions on, 26(9).
2009
- (Mueen et al., 2009) ⇒ Abdullah Mueen, Eamonn J. Keogh, and Nima Bigdely Shamlo. (2009). “Finding Time Series Motifs in Disk-Resident Data.” In: Proceedings of the Ninth IEEE International Conference on Data Mining (ICDM 2009). doi:10.1109/ICDM.2009.15
- QUOTE: Time series motifs are sets of very similar subsequences of a long time series.