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An User Interest Ontology Based on Trusted Friends Preferences for Personalized Recommendation

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Information Systems (EMCIS 2017)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 299))

Abstract

The importance of personalized recommender systems has recently increased and its role in providing better experiences to different users has been demonstrated. The quality of the recommendation can be guaranteed based on the help of user interpersonal interests in a social network. Information obtained about users and their friends makes it unnecessary to look for similar users and to measure their rating similarity. In our work, we have developed a trusted friend’s calculation method for determining social trusted friends by analyzing user’s profile on Facebook. We have also represented the user’s model as an ontology that takes into consideration all trusted friends’ preferences and the degree of trust between friends. Afterwards, we have used this ontology in a semantic tourism recommender system as an e-tourism tool able to recommend items based on the users’ preferences and their trusted friends’ preferences.

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Authors and Affiliations

  1. MIRACL Laboratory, University of Sfax, Sfax, Tunisia

    Mohamed Frikha, Mohamed Mhiri & Faiez Gargouri

Authors
  1. Mohamed Frikha
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  2. Mohamed Mhiri
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  3. Faiez Gargouri
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Corresponding author

Correspondence to Mohamed Frikha .

Editor information

Editors and Affiliations

  1. Department of Digital Systems, University of Piraeus, Piraeus, Greece

    Marinos Themistocleous

  2. Department of Management and Technology, Bocconi University, Milan, Italy

    Vincenzo Morabito

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Frikha, M., Mhiri, M., Gargouri, F. (2017). An User Interest Ontology Based on Trusted Friends Preferences for Personalized Recommendation. In: Themistocleous, M., Morabito, V. (eds) Information Systems. EMCIS 2017. Lecture Notes in Business Information Processing, vol 299. Springer, Cham. https://doi.org/10.1007/978-3-319-65930-5_5

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  • DOI: https://doi.org/10.1007/978-3-319-65930-5_5

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  • Online ISBN: 978-3-319-65930-5

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