Exploring Visualization Challenges for Interactive Recommender Systems

Users are faced with an increasing information overload problem in large, complex data collections. Recommender systems reduce the data set to a manageable size by providing suggestions to the user. Research in the last years has primarily focused on the quality of the underlying algorithms. Recent research started to focus on the user experience in recommender systems. The main challenges are transparency, controllability, explorability, and context-awareness. Interactive visualizations have the potential to address all of these issues. In this paper, we present three user interface concepts for different usage scenarios: movie, activities, and travel search. We propose a taxonomy of user interface building blocks to evaluate these concepts with regards to the visualization challenges.

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