Purpose :
While planning a tour to Pune in India, for the first time and we don’t know the best place according to our preferences and benefits. We may prefer to stay in a restaurant which is close to Market, or we may prefer cold breeze of a river or a lake. Yet, we may also like Park in our preferences or maybe Cafe or Dominoes for those who likes Pizza or Tea. We may have some other preferences or choices. So, what can we do? We can search the Internet and then research a bit, we may find some service providers or other groups where the people know the places according to the preference of the user. If one gets too lucky, they may have somebody known there, which is of course a local person to Pune who knows nook and corner of the city. The user, who wants to go for a vacation, might call his/her friend and may tell them to visit the best place, which is affordable for staying and which has the preferences according to the choices the users want and get their job done. But, in today’s busy world nobody cares to do such research and call friend, everybody is dependent on some application to find genuinely good places based on mass reviews from lot of local people. So, we come up with an application named Wisp. It is a standalone application based on Python programming language. It eliminates the overhead of doing research of a place for finding the hot-spots according to their preferences, which uses clustering algorithm along with fetching data from a remote server and visualises it in map. We provided certain features in the application to save that map and use it for future. Since, data is the new oil, we use data from a rich community maintained Foursquare API to visualise our map. We also think that if we could promote the use of Foursquare API, more users would actually use and provide data to the API by giving reviews, comments, etc, which will in turn increase the data and content of the API.
