A Novel Approach to Context Prediction in UBICOMP Environments
Stephan Sigg, Sandra Haseloff, Klaus David · 2006
The ability to predict future contexts significantly expands the possibilities of context-aware computing applications. However, an incorrect prediction may also mislead the application and may result in inappropriate application behaviour. We study influences on the prediction accuracy and propose a novel approach to context prediction in ubiquitous computing environments. In our paper we introduce a context time series prediction algorithm based on local alignment techniques. Our approach has the potential to improve the prediction accuracy since it explores the observed context history in more detail than current algorithms. In conclusion, we present simulation results that support our studies