In this work, we introduce the new problem of finding time series discords. Time series discords are subsequences of a longer time series that are maximally different to all the r...
Time series are a data type of utmost importance in many domains such as business management and service monitoring. We address the problem of visualizing large time-related data ...
Ming C. Hao, Umeshwar Dayal, Daniel A. Keim, Tobia...
Modern process and condition monitoring systems produce a huge amount of data which is hard to analyze manually. Previous analyzing techniques disregard time information and concen...
Time series are an important type of data with applications in virtually every aspect of the real world. Often a large number of time series have to be monitored and analyzed in p...
Ming C. Hao, Umeshwar Dayal, Daniel A. Keim, Tobia...
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...