A Personalized Tour Recommender in Python using Decision Tree

Abstract

A tourist recommendation system has been implemented based on python, Django framework and MySQL database. Firstly, crawler technology is used to crawl the ratings(reviews of customer experiences) information of TripAdvisor, and then the crawled ratings data is stored in MySQL. In the system, users can view the location, can view the opinion analytics(review packages), and collect the location information. According to the user's collection of location information, the decision tree  is used to recommend locations that may be of interest to users. If a new user enter his requirements then decision tree will predict best location based on his given input. Decision tree don’t need new users past experience data. Through the design of these functional modules, the whole tourist recommendation system is realized.