Geographic Information Science at the Heart of Europe

Part of the series Lecture Notes in Geoinformation and Cartography pp 39-53


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

  • Grant McKenzieAffiliated withDepartment of Geography, University of California Email author 
  • , Benjamin AdamsAffiliated withNational Center for Ecological Analysis and Synthesis (NCEAS), University of California
  • , Krzysztof JanowiczAffiliated withDepartment of Geography, University of California

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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.