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Evaluating the effectiveness of explanations for recommender systems : Methodological issues and empirical studies on the impact of personalization

<20>This paper in the top journal on personalization is the culmination of our work on explanations of recommendations. It extends our earlier work that won the James Chen best student paper award at the Adaptive Hypermedia 2008 conference (acceptance rate 28%). It also provides the scientific research behind Recommender Systems Handbook chapter “Group recommender systems: Combining individual models” (doi:10.1007/978-0-387-85820-3_21, 38 Google Scholar citations). Our research on explanations provided the inspiration for EPSRC funded project Scrutable Autonomous Systems (EP/J012084/1, £1M, Sep2012-15).