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Ubiquitous Fuzzy User Modeling for Multi-application Environments by Mining Socially Enhanced Online Traces

  • Conference paper
User Modeling, Adaptation, and Personalization (UMAP 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7379))

Abstract

In this paper, we propose an interoperable ubiquitous user model which illustrates different aspects of the individual’s interests, preferences and personality. It is constructed by mining socially enhanced online traces of the user and aggregating the partially obtained profiles. Those traces include actions performed and relationships established in the social web accounts in addition to the local machine traces such as bookmarks and web history. Moreover, we claim that mining the content in a context-aware approach and computing fuzziness values during the process results in a more reliable user profile.

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References

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Author information

Authors and Affiliations

  1. Tubitak Uzay Space Technologies Research Institute, Ankara, Turkey

    Hilal Tarakci & Nihan Kesim Cicekli

  2. Department of Computer Engineering, Middle East Technical University, Ankara, Turkey

    Hilal Tarakci & Nihan Kesim Cicekli

Authors
  1. Hilal Tarakci
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  2. Nihan Kesim Cicekli
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Editor information

Editors and Affiliations

  1. University of Aberdeen, Department of Computing Science, UK

    Judith Masthoff

  2. Center for Web Intelligence, School of Computing, DePaul University, 243 South Wabash Ave, Chicago, Illinois, 60604

    Bamshad Mobasher

  3. Polytechnique Montréal, 2500, chemin de Polytechnique, Montréal, (Québec), Canada

    Michel C. Desmarais

  4. Dept. of Computer Sciences, University of Quebec in Montreal, Canada

    Roger Nkambou

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© 2012 Springer-Verlag Berlin Heidelberg

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Tarakci, H., Cicekli, N.K. (2012). Ubiquitous Fuzzy User Modeling for Multi-application Environments by Mining Socially Enhanced Online Traces. In: Masthoff, J., Mobasher, B., Desmarais, M.C., Nkambou, R. (eds) User Modeling, Adaptation, and Personalization. UMAP 2012. Lecture Notes in Computer Science, vol 7379. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31454-4_42

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  • DOI: https://doi.org/10.1007/978-3-642-31454-4_42

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-31453-7

  • Online ISBN: 978-3-642-31454-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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