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Profile Matching Across Online Social Networks Based on Geo-Tags

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Advances in Nature and Biologically Inspired Computing

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 419))

Abstract

Profile matching in social networks is a challenging problem. There are many previous approaches but all of them rely on data, for which there is no ground truth. Profile information is provided by the users. Therefore, there is no certainty about the reliability of this information. For this reason, we suggest using timestamps, which are generated by the social network, and device-generated geo-tags. We take a closer look at various approaches for implementation of this profile matching algorithm. In addition, possibilities for evaluation of this algorithm are outlined afterwards.

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Notes

  1. 1.

    http://www.facebook.com.

  2. 2.

    http://newsroom.fb.com/company-info/.

  3. 3.

    http://www.flickr.com.

  4. 4.

    http://www.youtube.com.

  5. 5.

    http://www.twitter.com.

  6. 6.

    http://www.foursquare.com.

  7. 7.

    http://www.foaf-project.org/.

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Acknowledgments

The authors wish to thank the members of the Chair for Communication Systems and Network Security at the Universität der Bundeswehr München, headed by Prof. Dr. Gabi Dreo Rodosek, for helpful discussions and valuable comments on previous versions of this paper.

This work was partly funded by FLAMINGO, a Network of Excellence project (ICT-318488) supported by the European Commission under its Seventh Framework Program.

Author information

Authors and Affiliations

  1. Department for Communication Systems and Network Security, Faculty of Computer Science, Universität der Bundeswehr München, Neubiberg, Germany

    Robert Roedler, Dennis Kergl & Gabi Dreo Rodosek

Authors
  1. Robert Roedler
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  2. Dennis Kergl
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  3. Gabi Dreo Rodosek
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Corresponding author

Correspondence to Robert Roedler .

Editor information

Editors and Affiliations

  1. School of Mathematics, Statistics and CS, University of KwaZulu-Natal, Pietermaritzburg, South Africa

    Nelishia Pillay

  2. Sch of IT, Dept of CS, University of Pretoria, Pretoria, South Africa

    Andries P. Engelbrecht

  3. Sci N/w for Innova and Research Exc, Machine Intelligence Research Labs, Auburn, Washington, USA

    Ajith Abraham

  4. Department of Computing Sciences,, Nelson Mandela Metropolitan University, Port Elizabeth, South Africa

    Mathys C. du Plessis

  5. Faculty of Electrical Engineering and, Technical University of Ostrava, Ostrava-Poruba, Czech Republic

    Václav Snášel

  6. Fakulti Teknologi Maklumat dan Komunikas, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia

    Azah Kamilah Muda

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Roedler, R., Kergl, D., Rodosek, G.D. (2016). Profile Matching Across Online Social Networks Based on Geo-Tags. In: Pillay, N., Engelbrecht, A., Abraham, A., du Plessis, M., Snášel, V., Muda, A. (eds) Advances in Nature and Biologically Inspired Computing. Advances in Intelligent Systems and Computing, vol 419. Springer, Cham. https://doi.org/10.1007/978-3-319-27400-3_37

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  • DOI: https://doi.org/10.1007/978-3-319-27400-3_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27399-0

  • Online ISBN: 978-3-319-27400-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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