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Figure 1: Envisioned flow of the interactive visualization tool.  The proposed topic seeks to explore how an algorithm for big data visualization might be developed that combines the desirable properties of the existing algorithms for data mining for big data. We aim to create an interactive visualization tool for big data that incorporates user feedback into the algorithm to give some degree of freedom for the user to manipulate the visualization to their preference, as shown in figure 1. This is similar to your work in computer aided thinking where the thought spaces can be manipulated by the user. Some ideas for the user feedback would be to prioritize certain distances or fix certain points of interest and map the rest of the data points with respect to the points of interest.  The visualization would can  also be dynamic in the sense that users can interact with it using predefined actions like panning, actions. There are works that explores adding interactions such as  zooming, and rotating to see different views of the data and also expand summarized dataset to get more information. Zooming gives the user more information on a selected item and give less information on the other items not selected. An example of this is shown in Figure 2, where the original visualization contains many information and when you click a particular item it will only show the information for that particular item.