Skip to main content
SpringerLink
Log in
Book cover

International Conference on User Modeling, Adaptation, and Personalization

UMAP 2013: User Modeling, Adaptation, and Personalization pp 350–352Cite as

Leveraging Encyclopedic Knowledge for Transparent and Serendipitous User Profiles

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7899))

Abstract

The main contribution of this work is the comparison of different techniques for representing user preferences extracted by analyzing data gathered from social networks, with the aim of constructing more transparent (human-readable) and serendipitous user profiles. We compared two different user models representations: one based on keywords and one exploiting encyclopedic knowledge extracted from Wikipedia. A preliminary evaluation involving 51 Facebook and Twitter users has shown that the use of an encyclopedic-based representation better reflects user preferences, and helps to introduce new interesting topics.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Ferragina, P., Scaiella, U.: Tagme: on-the-fly annotation of short text fragments (by wikipedia entities). In: Proc. of the 19th ACM Int. Conf. on Information and Knowledge Management, pp. 1625–1628. ACM, New York (2010)

    Google Scholar 

  2. Gabrilovich, E., Markovitch, S.: Wikipedia-based semantic interpretation for natural language processing. Journal Artif. Intell. Res (JAIR) 34, 443–498 (2009)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of Milano-Bicocca, Italy

    Fedelucio Narducci

  2. University of Bari Aldo Moro, Italy

    Cataldo Musto, Giovanni Semeraro, Pasquale Lops & Marco de Gemmis

Authors
  1. Fedelucio Narducci
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Cataldo Musto
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Giovanni Semeraro
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Pasquale Lops
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Marco de Gemmis
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Computer and Information Science, University of Delaware, 19716, Delaware, DE, USA

    Sandra Carberry

  2. School of Computing, National College of Ireland, Mayor Street, IFSC, Dublin 1, Ireland

    Stephan Weibelzahl

  3. Dipartimento di Ingegneria, Roma Tre University, Via della Vasca Navale, 79, 00146, Rome, Italy

    Alessandro Micarelli

  4. Department of Computer Science, University of Bari Aldo Moro, 70126, Bari, Italy

    Giovanni Semeraro

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Narducci, F., Musto, C., Semeraro, G., Lops, P., de Gemmis, M. (2013). Leveraging Encyclopedic Knowledge for Transparent and Serendipitous User Profiles. In: Carberry, S., Weibelzahl, S., Micarelli, A., Semeraro, G. (eds) User Modeling, Adaptation, and Personalization. UMAP 2013. Lecture Notes in Computer Science, vol 7899. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38844-6_36

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-38844-6_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38843-9

  • Online ISBN: 978-3-642-38844-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation