Visualize It-Wise! An Iteration-Wise Computational Framework for Real-Time Visual Analytics
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Abstract Visual analytics has been gaining increasing interest due to its fascinating characteristic that leverages both humans’ visual perception and the power of computing. Although various computational methods are being proposed, they do not properly support visual analytics. One of the biggest obstacles towards their real-time visual analytic integration is their high computational complexity. As a way to tackle this problem, this paper presents an iteration-wise computational framework, motivated by the fact that most advanced computational methods work by refining the solution iteratively. By visually delivering the results for each iteration to users, the proposed framework enables users to quickly acquire the information that the computational method provides as well as the ability to interact with them in real time. We show the benefits of the proposed framework by using various dimension reduction and clustering methods.