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Explorative Analysis of Recommendations Through Interactive Visualization

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E-Commerce and Web Technologies (EC-Web 2016)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 278))

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Abstract

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.

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Notes

  1. 1.

    https://sourceforge.net/projects/vogoo/.

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Acknowledgments

The research leading to these results was supported by the “Bavarian State Ministry of Education, Science and the Arts” as part of the FORSEC research association. The authors would like to thank Kilian Müller and Regina Staller for the implementation of the prototype used in this paper.

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Authors and Affiliations

  1. Department of Information Systems, University of Regensburg, Regensburg, Germany

    Christian Richthammer & Günther Pernul

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  1. Christian Richthammer
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  2. Günther Pernul
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Correspondence to Christian Richthammer .

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Editors and Affiliations

  1. The Insight Centre for Data Analytics, University College Cork , Cork, Ireland

    Derek Bridge

  2. Data and Web Science Group, University of Mannheim, Mannheim, Germany

    Heiner Stuckenschmidt

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Richthammer, C., Pernul, G. (2017). Explorative Analysis of Recommendations Through Interactive Visualization. In: Bridge, D., Stuckenschmidt, H. (eds) E-Commerce and Web Technologies. EC-Web 2016. Lecture Notes in Business Information Processing, vol 278. Springer, Cham. https://doi.org/10.1007/978-3-319-53676-7_4

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  • DOI: https://doi.org/10.1007/978-3-319-53676-7_4

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-53676-7

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