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Skip to Search Results- 1Anomaly Detection
- 1Attribute-value pairs
- 1Clustering parameter
- 1Collision data
- 1Discord
- 1Event sequences
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Fall 2013
Many clustering techniques require parameter settings and depending on an algorithms sensitivity to the parameter, the choice of the parameter value can be very important. Several approaches have been proposed to find the “best” value of the clustering parameter for the different unsupervised...
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Fall 2013
Identifying spatial patterns of collisions is critical for improving the efficiency and effectiveness of traffic enforcement deployment and road safety. Recently, many studies have centred on finding locations with high collision concentration, so-called hotspots. However, most of them only focus...
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Spring 2013
We propose a two-phase method, called Multivariate Association Discovery (MAD), to mine temporal associations in multiple event sequences. It is assumed that a set of event sequences has been collected from an application, where each event has an id and an occurrence time. The goal is to detect...
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Fall 2013
Time series discords, as introduced in by Keogh et al. [5] is described as the subsequence in the time series which is maximally different from the rest of the subsequences. Discovery of time series discords has been applied to several diverse domains including space shuttle telemetry, industry,...