Multivariate time series (MTS) data sets are common in various multimedia, medical and financial application domains. These applications perform several data-analysis operations ...
Abstract-- Mining textual documents and time series concurrently, such as predicting the movements of stock prices based on the contents of the news stories, is an emerging topic i...
Gabriel Pui Cheong Fung, Jeffrey Xu Yu, Hongjun Lu
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...
This paper investigates cluster formation in decentralized sensor grids and focusses on predicting when the cluster formation converges to a stable configuration. The traffic volum...
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...