  The work of finding the best place according to user preference is a tedious
task. It needs manual research and lot of intuitive process to find the best
location according to some earlier knowledge about the place. It is mainly
about accessing publicly available spatial data, applying a simple algorithm to
summarize the data according to given preferences, and visualizing the result
on a map. We introduced JJCluster to eliminate the rigorous way of researching
about a place and visualizing the location in real time. This algorithm
successfully finds the heart of a city when used in Wisp application. The main
purpose of designing Wisp application is used for finding the perfect location
for a trip to unknown place which is nearest to a set of preferences. We also
discussed the various optimization algorithms that are pioneer of today's
dynamic programming and the need for visualization to find patterns when the
data is cluttered. Yet, this general clustering algorithm can be used in other
areas where we can explore every possible preference to maximize its utility.
