A Semantic Web Architecture for Context Recommendation System in E-learning Applications

Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 37)

Abstract

The widespread use of e-learning applications has put emphasis on the importance of having applications more personalized and adaptable to every learner needs. The one size fits all is no more working. Every learner should be delivered the right learning material that suits its learning context at the right time. The challenge is to incorporate the recommendation system in e-learning platforms in order to offer to learners a successful learning experience. In response to this challenge, in this paper, we propose a semantic web architecture of a context recommendation system in e-learning by means of which the learners will be offered learning content based on their profiles, activities and social interactions. The proposed architecture is a re-engineering of classical web architecture of current e-learning platforms. It’s based on semantic web technologies. It comprises an ontology that guarantees a shareable and reusable modeling of the learning context and OWL Rules filtering that will be used as a recommendation technique.

Keywords

Semantic web E-learning OWL ontology Recommendation system Context-aware SWRL 

References

  1. 1.
    Bouihi, B., Bahaj, M.: Building an e-learning system’s Owl ontology by exploring the UML model. J. Theor. Appl. Inf. Technol. 87(3), 380 (2016)Google Scholar
  2. 2.
    Soualah-Alila, F., Nicolle, C., Mendes, F.: Une approche Web sémantique et combinatoire pour un système de recommandation sensible au contexte appliqué à l’apprentissage mobile. In: 11 ème édition de l’atelier Fouille de Données Complexes, No. 47–58 (2014)Google Scholar
  3. 3.
    Grandbastien, M., Huynh-Kim-Bang, B., Monceaux, A.: Les ontologies du prototype LUISA, une architecture fondée sur des Web Services Sémantiques pour les ressources de formation. In: 19es Journées Francophones d’Ingénierie des Connaissances, pp. 61–72 (2008)Google Scholar
  4. 4.
    Ding, L., Finin, T., Joshi, A.: Analyzing social networks on the semantic web. IEEE Intell. Syst. (Trends & Controversies) 8(6), 815–820 (2004)Google Scholar
  5. 5.
    Buriano, L.: Exploiting social context information in context-aware mobile tourism guides. In: Proceedings of Mobile Guide (2006)Google Scholar
  6. 6.
    Yu, Z., Nakamura, Y., Jang, S., Kajita, S., Mase, K.: Ontology-based semantic recommendation for context-aware e-learning. In: Ubiquitous Intelligence and Computing, pp. 898–907 (2007)Google Scholar
  7. 7.
    Schmidt, A., Winterhalter, C.: User context aware delivery of e-learning material: approach and architecture. J. Univ. Comput. Sci. 10(1), 28–36 (2004)Google Scholar
  8. 8.
    Villalon, M.P., Suárez-Figueroa, M.C., García-Castro, R., Gómez-Pérez, A.: A context ontology for mobile environments (2010)Google Scholar
  9. 9.
    Benlamri, R., Zhang, X.: Context-aware recommender for mobile learners. Hum.-centric Comput. Inf. Sci. 4(1), 1–34 (2014)CrossRefGoogle Scholar
  10. 10.
    Shen, L.P., Shen, R.M.: Ontology-based learning content recommendation. Int. J. Contin. Eng. Educ. Life Long Learn. 15(3–6), 308–317 (2005)CrossRefGoogle Scholar
  11. 11.
    Henze, N., Dolog, P., Nejdl, W.: Reasoning and ontologies for personalized e-learning in the semantic web. Educ. Technol. Soc. 7(4), 82–97 (2004)Google Scholar
  12. 12.
    Shishehchi, S., Banihashem, S.Y., Zin, N.A.M.: A proposed semantic recommendation system for e-learning: a rule and ontology based e-learning recommendation system. In: 2010 International Symposium in Information Technology (ITSim), vol. 1, pp. 1–5. IEEE, June 2010Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Department of Mathematics and Computer Science, Faculty of Science and TechnologyUniversity Hassan 1stSettatMorocco

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