BULLSEYE

Targeting the tasty medium for everyone

One friend group -> Where should we eat? -Many food preferences, financial situations, and locations

Find Commonalities by using data analytics to pinpoint the cuisine, place, and price that suits everyone

Our process is easy

1. Select a group of friends
2. We compute your preferences
3. Browse our suggestions
4. Enjoy and get rewarded

Factors Analyzed:

• Cuisine & Price
• TensorFlow analyzes transaction history to discover shared preferences at an affordable price.
• Google Maps API finds matching places

How does it work?

• Location -> Centroid calculations on current and past user locations
• Rewards (Credit Card Bonuses)
• Matches users with sponsored spots for bonus points

Math & Algorithms Used

• Haversine’s Law
• Convex hull through Jarvis’ algorithm
• Remove restaurant outliers using elementary statistics
• Binary search :)
• Sigmoidal functions
• Ray casting

How to use:

1. Fork files
2. Install all requirements
3. Run flask in c1-summit folder in command prompt

flask run

4. Run Node.js in the public folder

npm start