We present a novel approach for clustering sequences of multi-dimensional trajectory data obtained from a sensor network. The sensory time-series data present new challenges to da...
We are studying long term sequence prediction (forecasting). We approach this by investigating criteria for choosing a compact useful state representation. The state is supposed t...
Mining for outliers in sequential databases is crucial to forward appropriate analysis of data. Therefore, many approaches for the discovery of such anomalies have been proposed. ...
Background: The Baum-Welch learning procedure for Hidden Markov Models (HMMs) provides a powerful tool for tailoring HMM topologies to data for use in knowledge discovery and clus...
Abstract. This paper describes a new segmentation technique for multidimensional dynamic data. One example of such data is a perfusion sequence where a number of 3D MRI volumes sho...
Yuri Boykov, Vivian S. Lee, Henry Rusinek, Ravi Ba...