Evening out with friends always comes to a challenge on picking the right place to hangout. Different apps provide different ratings based on their own criteria of ratings. Forsquity is an approach to combine all the ratings and get a bayesian inference out of the various ratings.

What it does

Forsquity has two aspects to it. First it fetches ratings from various rating sites. In this case, Foursquare, Google and Yelp. Then it applies these ratings to a bayesian algorithm at the back-end and produces a csv file from which the web page displays the information.

How we built it

The back-end process is built using python. The app gathers ratings and ratings count from Foursquare, Google Maps, Yelp, applies the simple bayesian inference and then produces a csv file. This csv file is consumed by the simple 1-page web application to display the various ratings including the bayesian rating.

Challenges we ran into

Combining and filtering out establishments after fetching their ratings was a big challenge, especially when the establishments have various naming convention in each rating site.

Accomplishments that we're proud of

I am happy to combine the ratings and get an unbiased view on ratings.

What we learned

Learned to fetch data from Foursquare, Google and Yelp and how to apply Bayesian inferences.

What's next for Forsquity

Make it a free app for general public use.

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