RESTAURANT RECOMMENDER
Restaurant discovery in a city is a difficult proposition for a diner with many things to consider -
- Rating
- Price points
- Customer Reviews
- Non-uniformity of the same restaurant listing across different sites
As a part of this project we aimed to aggregate data across different sites (Yelp, Zomato, TripAdvisor) and compare restaurants on a common platform.
The source code can be viewed here.
The what ?
To provide restaurant-goers a list of restaurants that accurately match their taste based on cuisine, popularity, reviews etc.
The how ?
By mining and summarizing restaurant data from multiple restaurant discovery sites, we were be able to provide our users the most accurate information for a restaurant listing
Data Sources:
- ZOMATO - ZOMATO API
- YELP - YELP FUSION API
- TRIP ADVISOR - KAGGLE
6 Product Features:
- Explore Top Restaurant Categories By Rating
- Explore Top Restaurant Categories By Price
- Explore TripAdvisor properties as Ratings (Converted Ranking to Ratings)
- Compare Ratings between 2 OR 3 Review sites
- View Top Review Comments by ZipCode (WordCloud)
- Combine it all - Get Top 3 Recommended Restaurants for Zomato, Yelp, TripAdvisor for a ZipCode, based on Ratings & Price
Technologies Used:
- Python 3
- NumPy, Seaborn, Matplotlib, Scipy, WordCloud
- Beautiful Soup
- Github
- Github Boards
- Jupyter Notebooks
