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ICDE
2009
IEEE

Temporal Outlier Detection in Vehicle Traffic Data

12 years 1 months ago
Temporal Outlier Detection in Vehicle Traffic Data
Outlier detection in vehicle traffic data is a practical problem that has gained traction lately due to an increasing capability to track moving vehicles in city roads. In contrast to other applications, this particular domain includes a very dynamic dimension: time. Many existing algorithms have studied the problem of outlier detection at a single instant in time. This study proposes a method for detecting temporal outliers with an emphasis on historical similarity trends between data points. Outliers are calculated from drastic changes in the trends. Experiments with real world traffic data show that this approach is effective and efficient.
Xiaolei Li, Zhenhui Li, Jiawei Han, Jae-Gil Lee
Added 20 Oct 2009
Updated 20 Oct 2009
Type Conference
Year 2009
Where ICDE
Authors Xiaolei Li, Zhenhui Li, Jiawei Han, Jae-Gil Lee
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