Method and system for optimizing the arrangement of spatial elements

1. In a data visualization system, executable on an electronic computing device, a method of analyzing and representing spatial data sets to optimize the arrangement of spatial elements which the data sets relate to, the representation enabling a user to visualize the spatial data sets in a manner that conveys information that would otherwise be lost, the method including the steps of:

retrieving data associated with the spatial data sets from a data storage module that is in communication with the data visualization system;

calculating a weight ranking of the performance of each of a plurality of predefined spatial areas;

determining lift values for the plurality of predefined spatial areas from the retrieved data using the weight ranking;

determining spatial performance values for the predefined spatial areas;

combining the determined lift values and spatial performance values to show the relationship between each of the spatial elements within the predefined spatial areas; and

displaying on a display device a graphical representation showing the predefined spatial areas, by:

rendering a rendered output including the graphical representation showing the relationship between each of the spatial elements within the predefined spatial areas; and

providing the rendered output to the display device and generating the graphical representation on the display device to allow the user to visualize the data.

2. The method of claim 1 wherein the fuzzy association rules apply spatial data within the retrieved data to a set of association rules to determine lift values for the predefined spatial areas.

3. The method of claim 1 further including the steps of monitoring the retrieved data over time and predicting changes to the weighted spatial relationships based on changes in the retrieved data.

4. The method of claim 1 further including the steps of applying a genetic algorithm to the retrieved data to form a spatial design, and subsequently performing the determination and combining steps.

5. The method of claim 1 further including the steps of determining isolated spatial areas and calculating weighted spatial relationships within the isolated spatial area.

6. The method of claim 1 further including the steps of cross tabulating the determined lift values and spatial performance values to show the relationship between each of the spatial elements within the predefined spatial areas.

7. A data visualization system comprising an electronic computing device including at least one processor and one or more memory devices, the one or more memory devices storing instructions executable by the at least one processor to perform the method according to claim 1 .

8. The data visualization system of claim 7 wherein the fuzzy association rules apply spatial data within the retrieved data to a set of association rules to determine lift values for the predefined spatial areas.

9. The data visualization system of claim 7 further arranged to perform the steps of monitoring the retrieved data over time and predicting changes to the weighted spatial relationships based on changes in the retrieved data.

10. The data visualization system of claim 7 further arranged to perform the steps of applying a genetic algorithm to the retrieved data to form a spatial design, and subsequently performing the determination and combining steps.

11. The data visualization system of claim 7 further arranged to perform the steps of determining isolated spatial areas and calculating weighted spatial relationships within the isolated spatial area.

12. The data visualization system of claim 7 further arranged to perform the steps of cross tabulating the determined lift values and spatial performance values to show the relationship between each of the spatial elements within the predefined spatial areas.