  In this short paper, we propose the split-diffuse (SD) algorithm that takes
the output of an existing word embedding algorithm, and distributes the data
points uniformly across the visualization space. The result improves the
perceivability and the interactability by the human.
  We apply the SD algorithm to analyze the user behavior through access logs
within the cyber security domain. The result, named the topic grids, is a set
of grids on various topics generated from the logs. On the same set of grids,
different behavioral metrics can be shown on different targets over different
periods of time, to provide visualization and interaction to the human experts.
  Analysis, investigation, and other types of interaction can be performed on
the topic grids more efficiently than on the output of existing dimension
reduction methods. In addition to the cyber security domain, the topic grids
can be further applied to other domains like e-commerce, credit card
transaction, customer service to analyze the behavior in a large scale.
