A Thematic Approach to User Similarity Built on Geosocial Check-ins

  • Grant McKenzie
  • Benjamin Adams
  • Krzysztof Janowicz
Chapter
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Computing user similarity is key for personalized location-based recommender systems and geographic information retrieval. So far, most existing work has focused on structured or semi-structured data to establish such measures. In this work, we propose topic modeling to exploit sparse, unstructured data, e.g., tips and reviews, as an additional feature to compute user similarity. Our model employs diagnosticity weighting based on the entropy of topics in order to assess the role of commonalities and variabilities between similar users. Finally, we offer a validation technique and results using data from the location-based social network Foursquare.

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Grant McKenzie
    • 1
  • Benjamin Adams
    • 2
  • Krzysztof Janowicz
    • 1
  1. 1.Department of GeographyUniversity of CaliforniaSanta BarbaraUSA
  2. 2.National Center for Ecological Analysis and Synthesis (NCEAS)University of CaliforniaSanta BarbaraUSA

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