The search for unknown frequent pattern is one of the core activities in many time series data mining processes. In this paper we present an extension of the pattern discovery pro...
We are developing technology for generating English textual summaries of time-series data, in three domains: weather forecasts, gas-turbine sensor readings, and hospital intensive...
Somayajulu Sripada, Ehud Reiter, Jim Hunter, Jin Y...
In this paper, we present an abstract framework for online approximation of time-series data that yields a unified set of algorithms for several popular models: data streams, amnes...
Time series prediction is an important issue in a wide range of areas. There are various real world processes whose states vary continuously, and those processes may have influenc...
Many time series prediction methods have focused on single step or short term prediction problems due to the inherent difficulty in controlling the propagation of errors from one ...