Outlier Detection for Temporal Data: A Survey
Microsoft (India) · Microsoft (United States) · +2 more institutions
Abstract
In the statistics community, outlier detection for time series data has been studied for decades. Recently, with advances in hardware and software technology, there has been a large body of work on temporal outlier detection from a computational perspective within the computer science community. In particular, advances in hardware technology have enabled the availability of various forms of temporal data collection mechanisms, and advances in software technology have enabled a variety of data management mechanisms. This has fueled the growth of different kinds of data sets such as data streams, spatio-temporal data, distributed streams, temporal networks, and time series data, generated by a multitude of…
Citation impact
- FWCI
- 72.72
- Percentile
- 100%
- References
- 211
Authors
4Topics & keywords
- Computer science
- Anomaly detection
- Outlier
- Temporal database
- Data mining
- Data stream mining
- Time series
- Software