  The search for pulsars produces a massive amount of data which needs to be
processed and analyzed. The limited speed of manual observation necessitates
the involvement of large numbers of people to keep up with data collection.
This paper turns to the automated alternative by examining the methodology of
an algorithm built to automatically filter through processed and reduced data,
which then presents the most promising data to human observers for confirmation
and more complex analysis. The benefits and shortcomings of this algorithm are
examined while explaining plans for future testing.
