User Model Enrichment for Venue Recommendation

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9994)


An important task in recommender systems is suggesting relevant venues in a city to a user. These suggestions are usually created by exploiting the user’s history of preferences, which are, for example, collected in previously visited cities. In this paper, we first introduce a user model based on venues’ categories and their descriptive keywords extracted from Foursquare tips. Then, we propose an enriched user model which leverages the users’ reviews from Yelp. Our participation in the TREC 2015 Contextual Suggestion track, confirmed that our model outperforms other approaches by a significant margin.


Support Vector Machine Recommender System Support Vector Machine Classifier Latent Dirichlet Allocation Online Review 
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 AG 2016

Authors and Affiliations

  • Mohammad Aliannejadi
    • 1
  • Ida Mele
    • 1
  • Fabio Crestani
    • 1
  1. 1.Faculty of InformaticsUniversità della Svizzera ItalianaLuganoSwitzerland

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