By Topic

Minimising the Context Prediction Error

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Sigg, S. ; Dept. of Commun. Technol., Kassel Univ. ; Haseloff, S. ; David, K.

Context prediction mechanisms proactively provide information on future contexts. Due to this knowledge novel applications become possible that provide services with proactive knowledge to users. The most serious problem of context prediction mechanisms lies in a basic property of prediction itself. A prediction is always a guess. Since erroneous predictions may cause the application to behave insufficiently, prediction errors have to be minimised. The accuracy of prediction is seriously affected by the reliability of the context data that is utilised by the method. We study two paradigms for context prediction and compare their potential prediction accuracy. We show that the designer of context prediction architectures has to choose wisely as to which prediction paradigm to follow in order to maximise the accuracy of the whole architecture. We also introduce a simulation environment and present simulation results that support the gained insights regarding context prediction.

Published in:

Vehicular Technology Conference, 2007. VTC2007-Spring. IEEE 65th

Date of Conference:

22-25 April 2007