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Leveraging Encyclopedic Knowledge for Transparent and Serendipitous User Profiles

  • Conference paper
User Modeling, Adaptation, and Personalization (UMAP 2013)

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.

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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)

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© 2013 Springer-Verlag Berlin Heidelberg

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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

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  • 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)

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