Restaurant finder featureReviews

• Built a web crawler using Scrapy to collect restaurant information and reviews from TripAdvisor.
• Performed web scraping, cleaning and preprocessing of restaurant data before storing in MongoDB.
• Removed stop words, punctuations, special characters, numbers, and white-spaces from user reviews, and built a corpus applying tokenization and stemming.
• Identified key restaurant features from user reviews using Apriori algorithm and NLP.
• Generated summarized reviews based on frequent restaurant features.
• Created intelligent dashboards using Tableau to discover top restaurants by positive and negative reviews, cuisine, feature/meal, price, and location.
• Built a Flask application for users to search for restaurants based on their preference. The application also displays a feature based reviews for the searched restaurant and provides restaurant statistics by city along with other key information.

1. Restaurant Scraper
2. Data Cleaning and Processing for Analysis
3. Feature Review and Sentiment Analysis
4. Web Application

1. UK Map - Filter by City/Price/Cuisine/Meal/Feature
2. Restaurant Statistics - Filter by City
3. Categorical/Positive/Negative Review Count - Filter by City

Python

Scrapy, MongoDB, Flask

Tableau, MacOS Terminal(Vim)