The parallel explosions of interest in streaming data, and data mining of time series have had surprisingly little intersection. This is in spite of the fact that time series data...
Jessica Lin, Eamonn J. Keogh, Stefano Lonardi, Bil...
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
With the advance of hardware and communication technologies, stream time series is gaining ever-increasing attention due to its importance in many applications such as financial da...
Previous work on text mining has almost exclusively focused on a single stream. However, we often have available multiple text streams indexed by the same set of time points (call...
Xuanhui Wang, ChengXiang Zhai, Xiao Hu, Richard Sp...
We consider the problem of nding rules relating patterns in a time series to other patterns in that series, or patterns in one series to patterns in another series. A simple examp...
Gautam Das, King-Ip Lin, Heikki Mannila, Gopal Ren...