Map Based Visualization of Product Catalogs

  • Martijn Kagie
  • Michiel van Wezel
  • Patrick J.F. Groenen


Traditionally, recommender systems present recommendations in ranked lists to the user. In content- and knowledge-based recommender systems, these lists are often sorted on some notion of similarity with a query, ideal product specification, or sample product. However, a lot of information is lost in this way, since two products with the same similarity to a query can differ from this query on a completely different set of product characteristics. When using a two dimensional map based visualization of the recommendations, it is possible to retain part of this information. In the map, we can then position recommendations that are similar to each other in the same area of the map.


Recommender System Memory Size Poisson Regression Model Numerical Attribute Dissimilarity Measure 
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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We thank Compare Group for making their product catalog and clickstream log files available to us.


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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Martijn Kagie
    • 1
  • Michiel van Wezel
    • 1
  • Patrick J.F. Groenen
    • 1
  1. 1.Econometric Institute, Erasmus University RotterdamRotterdamThe Netherlands

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