Hotel Recommendation and Sentiment Analysis
The main aim of this project is to conduct a deep analysis of Hotel Booking Systems (Websites), to interpret customer booking patterns. This is followed by taking user’s preferences and recommending a Hotel customized to the user’s needs using Machine Learning Models. The project then goes a step further and takes user’s feedback of the hotel, which is further analyzed under a Sentiment Analysis to categorize the experience as good or bad. Along with this Machine Learning model, the project also carries out an extensive analysis of the scraped data from different websites to highlight various patterns of hotel booking and reviews collected. Finally, the Recommendation System is given a GUI front in the form of a website.