Approach comparison on context-aware computing with uncertainty

  • Authors:

  • Zongjie Wang;Degan Zhang;Aili Li;Xiaobin Huang;Hongtao Peng

  • Affiliations:

  • Computer Science Department, University of Science and Technology Beijing;-;Computer Science Department, University of Science and Technology Beijing and Key Lab of Traffic Plan. & Man. of Jiangsu, Southeast University, Nanjing;Computer Science Department, University of Science and Technology Beijing;Computer Science Department, CNPC Managers Training Institute, Beijing

  • Venue:
  • Edutainment'07 Proceedings of the 2nd international conference on Technologies for e-learning and digital entertainment
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

Context-aware computing with uncertainty includes forming model, fusing of aware context, managing context information and so on. Approachcom-parison on computing of aware context with uncertainty for makingdynamic deci-sion is focused in this paper. We compare dynamic context-awarecomputing with improved Random Set Theory (RST) and extended D-SEvidence Theory (EDS). We give new modeling mode based on RST for awarecontext and our computing approach of modeled aware context, extend classicD-S Evidence Theory after considering context's feature. Then comparerelative computing methods, enu-merate experimental examples and give theevaluation. By comparisons, the more validity of new context-aware computingapproach based on RST than EDS with uncertainty information has been testedsuccessfully.