Spatial clustering to uncluttering map visualization in SOLAP

By Silva, R.; Moura-Pires, J.; Yasmina Santos, M.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)



The main purpose of SOLAP concept was to take advantage of the map visualization improving the analysis of data and enhancing the associated decision making process. However, in this environment, the map can easily become cluttered losing the benefits that triggered the appearance of this concept. In order to overcome this problem we propose a post-processing stage, which relies on a spatial clustering approach, to reduce the number of values to be visualized when this number is inadequate to a properly map analysis. The results obtained so far show that the usage of the post–processing stage is very useful to maintain a map suitable to the user’s cognitive process. In addition, a novel heuristic to identify the threshold value from which the clusters must be generated was developed.


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