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Age, Gender, Race and Smile Prediction Based on Social Textual and Visual Data Analyzing

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Intelligent Systems Design and Applications (ISDA 2016)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 557))

Abstract

In a relatively short period of time, we have observed the explosion of social network platforms which have acquired a prominent role in the people’s daily life. In this context, each Facebook user can easily access and control the data shared on his/her corresponding profile. However, despite the large amount of information contained in Facebook user profile, this information is unstructured and not organized. In this paper, we propose a user ontology profiling in social networks by using a framework containing a Facebook application written in PHP, which accumulates all the equivalent shared data and stocks it in a not only SQL database Cassandra used for further analysis.

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Authors and Affiliations

  1. REGIM-Lab.: Research Groups in Intelligent Machines, University of Sfax National School of Engineers (ENIS), BP 1173, 3038, Sfax, Tunisia

    Onsa Lazzez, Wael Ouarda & Adel M. Alimi

Authors
  1. Onsa Lazzez
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  2. Wael Ouarda
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  3. Adel M. Alimi
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Corresponding author

Correspondence to Onsa Lazzez .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Instituto Superior de Engenharia do Port, Porto, Portugal

    Ana Maria Madureira

  2. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  3. Polytechnic Institute of Porto, Felgueiras, Portugal

    Dorabela Gamboa

  4. Campus of Gualtar, University of Minho, Braga, Portugal

    Paulo Novais

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Lazzez, O., Ouarda, W., Alimi, A.M. (2017). Age, Gender, Race and Smile Prediction Based on Social Textual and Visual Data Analyzing. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_21

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  • DOI: https://doi.org/10.1007/978-3-319-53480-0_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-53479-4

  • Online ISBN: 978-3-319-53480-0

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