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Knowledge-Based Leisure Time Recommendations in Social Networks

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Current Trends on Knowledge-Based Systems

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 120))

Abstract

We introduce a novel knowledge-based recommendation algorithm for leisure time information to be used in social networks, which enhances the state-of-the-art in this algorithm category by taking into account (a) qualitative aspects of the recommended places (restaurants, museums, tourist attractions etc.), such as price, service and atmosphere, (b) influencing factors between social network users, (c) the semantic and geographical distance between locations and (d) the semantic categorization of the places to be recommended. The combination of these features leads to more accurate and better user-targeted leisure time recommendations.

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Author information

Authors and Affiliations

  1. Department of Informatics and Telecommunications, University of Athens, Athens, Greece

    Dionisis Margaris & Panagiotis Georgiadis

  2. Department of Informatics and Telecommunications, University of the Peloponnese, Tripoli, Greece

    Costas Vassilakis

Authors
  1. Dionisis Margaris
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  2. Costas Vassilakis
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  3. Panagiotis Georgiadis
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Correspondence to Dionisis Margaris .

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Editors and Affiliations

  1. 852 Col. Emiliano Zapata, Instituto Tecnologico de Orizaba 852 Col. Emiliano Zapata, Orizaba, Veracruz, Mexico

    Giner Alor-Hernández

  2. Campus de Espinardo s/n., Facultad de Informática Campus de Espinardo s/n., Murcia, Spain

    Rafael Valencia-García

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Margaris, D., Vassilakis, C., Georgiadis, P. (2017). Knowledge-Based Leisure Time Recommendations in Social Networks. In: Alor-Hernández, G., Valencia-García, R. (eds) Current Trends on Knowledge-Based Systems. Intelligent Systems Reference Library, vol 120. Springer, Cham. https://doi.org/10.1007/978-3-319-51905-0_2

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  • DOI: https://doi.org/10.1007/978-3-319-51905-0_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-51904-3

  • Online ISBN: 978-3-319-51905-0

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