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Recommendation of Text Tags in Social Applications Using Linked Data

  • Andrea Calì
  • Stefano Capuzzi
  • Mirko Michele Dimartino
  • Riccardo Frosini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8295)

Abstract

We present a recommender system that suggests geo-located text tags by using linguistic information extracted from Linked Data sets available on the Web. The recommender system performs tag matching by measuring the semantic similarity of natural language texts. Our approach evaluates similarity using a technique that compares sentences taking into account their grammatical structure.

Keywords

Recommender System Semantic Similarity Link Data Social Application Link Open Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Andrea Calì
    • 1
    • 2
  • Stefano Capuzzi
    • 3
  • Mirko Michele Dimartino
    • 1
  • Riccardo Frosini
    • 1
  1. 1.Dept. of Computer Science and Inf. Syst.Birkbeck, University of LondonUK
  2. 2.Oxford-Man Institute of Quantitative FinanceUniversity of OxfordUK
  3. 3.Dipartimento di Ingegneria dell’InformazioneUniversità di BresciaItaly

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