Vol.9, No.3, August 2020.                                                                                                                                                                                ISSN: 2217-8309

                                                                                                                                                                                                                        eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Contextual Information Retrieval within Recommender System: Case Study "E-learning System"


Mourad Brik, Mohamed Touahria


© 2020 Mourad Brik, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 9, Issue 3, Pages 1150-1162, ISSN 2217-8309, DOI: 10.18421/TEM93-41, August 2020.


Received: 02 February 2020.

Revised:   28 May 2020.
Accepted: 05 June 2020.
Published: 28 August 2020.




This paper focuses on monitoring and analyzing user activities on collaborative filtering -based recommender system in order to guess suitable and unsuitable items' context information using rating matrix which makes more efficient adaptation task. An ontology-based user profile and rules-based context modeling for reasoning about context information is proposed in this research work, in addition to an investigation to apply Semantic Web technologies in user modeling and context reasoning. This proposal is applied in education field in which we have designed an authoring tool for learning objects within ubiquitous environment. This system aims to improve the learning object production task (creation, review, edition…) on behalf of technologies offered by collaborative filtering systems as well as user behaviors monitoring to improve the recommendation process.


Keywords –collaborative filtering, user profile, context aware, rule-based ontology, user behaviors.



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