Budget and Experience Based Travel Planner Using Collaborative Filtering

Abstract

Travellers in the modern era face many challenges. Budget and time are the major constraints for a traveller. So a good travel plan should be satisfying these constraints and provide maximum enjoyment to the traveller. The proposed ‘Budget and Experience-based Travel Planner’ allows a traveller to create a travel plan that satisfies the above-mentioned constraints as well as other factors such as the experience of the traveller. The collected data from different sources are filtered and places that have missing fields that are relevant such as tags, district, coordinates, rating, reviews, etc are removed along with places having irrelevant tags. After filtering, the database contains over 600 destinations with 77 unique tags. Using suitable machine learning algorithms considering the constraints, the recommendation engine recommends places. We have created a routing algorithm which minimizes the distance covered to reach the different destinations considering the various cases that could happen. Suitable algorithms are used for scheduling the travel itinerary. The time, budget and destination are provided by the user and a suitable travel plan is provided back to the user.