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...
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 ...
We study the problem of correlating micro-blogging activity with stock-market events, defined as changes in the price and traded volume of stocks. Specifically, we collect messa...
Eduardo J. Ruiz, Vagelis Hristidis, Carlos Castill...
This paper describes our work in learning online models that forecast real-valued variables in a high-dimensional space. A 3GB database was collected by sampling 421 real-valued s...