Explorative Analysis of Recommendations Through Interactive Visualization

Even though today’s recommender algorithms are highly sophisticated, they can hardly take into account the users’ situational needs. An obvious way to address this is to initially inquire the users’ momentary preferences, but the users’ inability to accurately state them upfront may lead to the loss of several good alternatives. Hence, this paper suggests to generate the recommendations without such additional input data from the users and let them interactively explore the recommended items on their own. To support this explorative analysis, a novel visualization tool based on treemaps is developed. The analysis of the prototype demonstrates that the interactive treemap visualization facilitates the users’ comprehension of the big picture of available alternatives and the reasoning behind the recommendations. This helps the users get clear about their situational needs, inspect the most relevant recommendations in detail, and finally arrive at informed decisions.