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Evidential Multi-relational Link Prediction Based on Social Content

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Foundations of Intelligent Systems (ISMIS 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11177))

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Abstract

A novel framework to address the link prediction problem in multiplex social networks is introduced. In this framework, uncertainty found in social data due to noise, missing information and observation errors is handled by the belief function theory. Despite the numerous published studies on link prediction, few research are concerned with social data imperfections issues which cause distortions in social networks structures and probably inaccurate results. In addition, most works focus on similarity scores based on network topology whereas social networks include rich content which may add semantic to the analysis and enhance results. To this end, we develop a link prediction method that combine network topology and social content to predict new links existence along with their types in multiplex social networks. Structural and social neighbors information are gathered and pooled using belief function theory combination rules. It is subsequently revised according to global information about the multiplex. Experiments performed on real world social data show that our approach works well and enhances the prediction accuracy.

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Authors and Affiliations

  1. LARODEC, Institut Supérieur de Gestion de Tunis, Université de Tunis, Tunis, Tunisia

    Sabrine Mallek, Imen Boukhris & Zied Elouedi

  2. Univ. Artois, EA 3926, Laboratoire de Génie Informatique et d’Automatique de l’Artois (LGI2A), 62400, Béthune, France

    Sabrine Mallek & Eric Lefevre

Authors
  1. Sabrine Mallek
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  2. Imen Boukhris
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  3. Zied Elouedi
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  4. Eric Lefevre
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Corresponding author

Correspondence to Sabrine Mallek .

Editor information

Editors and Affiliations

  1. Università degli Studi di Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

  2. American University, Washington, DC, USA

    Nathalie Japkowicz

  3. Hong Kong Baptist University, Kowloon, Hong Kong

    Jiming Liu

  4. University of Cyprus, Nicosia, Cyprus

    George A. Papadopoulos

  5. University of North Carolina, Charlotte, NC, USA

    Zbigniew W. Raś

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Mallek, S., Boukhris, I., Elouedi, Z., Lefevre, E. (2018). Evidential Multi-relational Link Prediction Based on Social Content. In: Ceci, M., Japkowicz, N., Liu, J., Papadopoulos, G., Raś, Z. (eds) Foundations of Intelligent Systems. ISMIS 2018. Lecture Notes in Computer Science(), vol 11177. Springer, Cham. https://doi.org/10.1007/978-3-030-01851-1_32

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  • DOI: https://doi.org/10.1007/978-3-030-01851-1_32

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  • Online ISBN: 978-3-030-01851-1

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