Abstract
The tremendous growth of online social networks all over the world has created a new place and means of social interaction and communication among people. This paper aims to improve traditional recommender systems by incorporating information in social networks, including user preferences and influences from social friends. A user interest ontology is developed to make personalized recommendations out of such information. In this paper, we present a social recommender system employing a user interest ontology. Our system can improve the quality of recommendation for Tunisian tourism domain. Finally, our social recommendation algorithm will be implemented in order to be used in a Tunisia tourism Website to assist users interested in visiting Tunisian places.
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Frikha, M., Mhiri, M., Gargouri, F. (2015). Designing a User Interest Ontology-Driven Social Recommender System: Application for Tunisian Tourism. In: Bajo, J., et al. Trends in Practical Applications of Agents, Multi-Agent Systems and Sustainability. Advances in Intelligent Systems and Computing, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-319-19629-9_18
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DOI: https://doi.org/10.1007/978-3-319-19629-9_18
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19628-2
Online ISBN: 978-3-319-19629-9
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