Large and high-dimensional data sets mapped to low-dimensional visualizations often result in perceptual ambiguities. One such ambiguity is overlap or occlusion that occurs when the number of records exceeds the number of unique locations in the presentation or when there exist two or more records that map to the same location. To lessen the affect of occlusion, non-standard visual attributes (i.e. shading and/or transparency) are applied, or such records may be remapped to a corresponding jittered location. The resulting mapping efficiently portrays the crowding of records but fails to provide the insight into the relationship between the neighboring records. We introduce a new interactive technique that intelligibly organizes overlapped points, a neural network-based Smart Jittering algorithm. We demonstrate this technique on a scatter plot, the most widely used visualization. The algorithm can be applied to other one, two, and multi-dimensional visualizations which represent data as points, including 3-dimensional scatter plots, RadViz, polar coordinates.