Abstract
User data can be acquired from various domains. This data is characterized by a combination of demographics such as age and occupation and user actions such as rating a movie, reviewing a restaurant or buying groceries. User data is appealing to analysts in their role as data scientists who seek to conduct large-scale population studies, and gain insights on various population segments. It is also appealing to novice users in their role as information consumers who use the social Web for routine tasks such as finding a book club or choosing a restaurant.
User data exploration has been formulated as identifying group-level behavior such as Asian women who publish regularly in databases. Group-level exploration enables new findings and addresses issues raised by the peculiarities of user data such as noise and sparsity. I will review our work on one-shot [1,2,3,4] and interactive [5] user data exploration. I will then describe the challenges of developing a visual analytics tool for finding and connecting users and groups.
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Notes
- 1.
We do not know Mary personally but she is a real user on BookCrossing.
- 2.
Martin Theobald was indeed the WebDB PC chair in 2014!
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Amer-Yahia, S. (2017). Toward Interactive User Data Analytics. In: Calì, A., Wood, P., Martin, N., Poulovassilis, A. (eds) Data Analytics. BICOD 2017. Lecture Notes in Computer Science(), vol 10365. Springer, Cham. https://doi.org/10.1007/978-3-319-60795-5_1
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DOI: https://doi.org/10.1007/978-3-319-60795-5_1
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