A good distance measure for time series needs to properly incorporate the temporal structure, and should be applicable to sequences with unequal lengths. In this paper, we propose...
Zhengdong Lu, Todd K. Leen, Yonghong Huang, Deniz ...
Modern approaches to treating genetic disorders, cancers and even epidemics rely on a detailed understanding of the underlying gene signaling network. Previous work has used time s...
David Oviatt, Mark J. Clement, Quinn Snell, Kennet...
We outline an incremental learning algorithm designed for nonstationary environments where the underlying data distribution changes over time. With each dataset drawn from a new e...
Matthew T. Karnick, Michael Muhlbaier, Robi Polika...
We introduce a method to discover optimal local patterns, which concisely describe the main trends in a time series. Our approach examines the time series at multiple time scales ...
There has been much recent interest in retrieval of time series data. Earlier work has used a fixed similarity metric (e.g., Euclidean distance) to determine the similarity betwee...