Abstract
Users’ download history is a primary data source for analyzing user interests. Recent work has shown that user interests are indeed time varying, and accurate profiling of user interest drifts requires the temporal dynamic analyses. We have proposed a visualization approach to analyzing user interest drifts from the download history, taking music as an example, and studied how to depict the underlying relevances among the downloaded music items to identify the drifts. We designed three new kinds of plots to display the music download history of one user, namely Bean plot, Transitional Pie plot, and Instrument plot. In this paper, we report our conducted user studies that ask normal users to visually analyze the download history of other users in a given real-world data set. User studies are performed in a learning-practice-test workflow. The results demonstrate the feasibility of our visualization design.
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Notes
- 1.
All the plots can be accessed from http://staff.ustc.edu.cn/%7Edongeliu/stuff/userStudyPlots.pdf.
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Acknowledgment
This work was supported by National Program on Key Basic Research Projects (973 Program) under No. 2015CB351800, by Natural Science Foundation of China (NSFC) under No. 61303149 and No. 61331017, and by the Fundamental Research Funds for the Central Universities.
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Liu, D., Zhang, J. (2016). Visual Analyses of Music Download History: User Studies. In: Tian, Q., Sebe, N., Qi, GJ., Huet, B., Hong, R., Liu, X. (eds) MultiMedia Modeling. MMM 2016. Lecture Notes in Computer Science(), vol 9516. Springer, Cham. https://doi.org/10.1007/978-3-319-27671-7_6
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