Proactive Mobile Learning on the Semantic Web

Rachid Benlamri, Jawad Berri, Xiaoyun Zhang



Flexible and personalized instruction is one of the most important requirements to next generation intelligent educational systems. The intelligence of any e-learning system is thus measured by its ability to sense, aggregate and use, the various contextual elements to characterize the learner, and to react accordingly by providing a set of customized learning services. In this paper we propose a proactive context aware mobile learning system on the Semantic Web. The contribution of this work is a combined model using both a probabilistic learning technique and an ontology-based approach to enable intelligent context processing and management. The system uses a Naïve Bayesian classifier to recognize high level contexts in terms of their constituent atomic context elements. Recognized contexts are then interpreted as triggers of actions yielding a Web service composition. This is achieved by reasoning on the ontological description of atomic context elements participating in the high level context.


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Paper Citation

in Harvard Style

Benlamri R., Berri J. and Zhang X. (2007). Proactive Mobile Learning on the Semantic Web . In Proceedings of the 1st International Joint Workshop on Wireless Ubiquitous Computing - Volume 1: WUC, (ICEIS 2007) ISBN 978-972-8865-94-8, pages 63-73. DOI: 10.5220/0002434400630073

in Bibtex Style

author={Rachid Benlamri and Jawad Berri and Xiaoyun Zhang},
title={Proactive Mobile Learning on the Semantic Web},
booktitle={Proceedings of the 1st International Joint Workshop on Wireless Ubiquitous Computing - Volume 1: WUC, (ICEIS 2007)},

in EndNote Style

JO - Proceedings of the 1st International Joint Workshop on Wireless Ubiquitous Computing - Volume 1: WUC, (ICEIS 2007)
TI - Proactive Mobile Learning on the Semantic Web
SN - 978-972-8865-94-8
AU - Benlamri R.
AU - Berri J.
AU - Zhang X.
PY - 2007
SP - 63
EP - 73
DO - 10.5220/0002434400630073