Context prediction is a promoting research topic with a lot of challenges and opportunities. Indeed, with the constant evolution of context-aware systems, context prediction remains a complex task due to the lack of formal approach. In this paper, we propose a new approach to enhance context prediction using a probabilistic temporal logic and model checking. The probabilistic temporal logic PCTL is used to provide an efficient expressivity and a reasoning based on temporal logic in order to fit with the dynamic and non-deterministic nature of the system's environment. Whereas, the probabilistic model checking is used for automatically verifying that a probabilistic system satisfies a property with a given likelihood. Our new approach allows a formal expressivity of a multidimensional context prediction. Tested on real data our model was able to achieve 78% of the future activities prediction accuracy.
Publié le : 2019-02-05
Classification:
other areas of Computing and Informatics,
Context prediction, logic, PCTL, pervasive system, context-aware system, stochastic, transition model,
68T01, 68T30, 68T37, 68U35
@article{cai2018_6_1411,
author = {Darine Ameyed; Synchromedia Laboratory, Quebec University, \'Ecole de Technologie Sup\'erieure, Montr\'eal and Moeiz Miraoui; Higher Institute of Applied Science and Technology of Gafsa, University of Gafsa and Atef Zaguia; College of Computers and Information Technology, Taif University, Hawiyah, Taif and Fehmi Jaafar; Faculty of Management of Concordia University of Edmonton and Chakib Tadj; MMS Laboratory, Quebec University, \'Ecole de Technologie Sup\'erieure, Montr\'eal},
title = {Using Probabilistic Temporal Logic PCTL and Model Checking for Context Prediction},
journal = {Computing and Informatics},
volume = {37},
number = {6},
year = {2019},
language = {en},
url = {http://dml.mathdoc.fr/item/cai2018_6_1411}
}
Darine Ameyed; Synchromedia Laboratory, Quebec University, École de Technologie Supérieure, Montréal; Moeiz Miraoui; Higher Institute of Applied Science and Technology of Gafsa, University of Gafsa; Atef Zaguia; College of Computers and Information Technology, Taif University, Hawiyah, Taif; Fehmi Jaafar; Faculty of Management of Concordia University of Edmonton; Chakib Tadj; MMS Laboratory, Quebec University, École de Technologie Supérieure, Montréal. Using Probabilistic Temporal Logic PCTL and Model Checking for Context Prediction. Computing and Informatics, Tome 37 (2019) no. 6, . http://gdmltest.u-ga.fr/item/cai2018_6_1411/