Abstract
Planning plays the major role in organizing a trip or an outing. Though there are various resources in the web, and various travel agencies that provide planned trips, the automation provided by them is low. This project is an attempt to build a comprehensive travel recommendation system, which builds the itinerary to the user based on his priorities and inputs, along with providing personalized recommendations. The project makes use of machine learning algorithms like collaborative filtering and content-based filtering, along with Google APIs to build the itinerary and provide recommendations.
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Chaitra, D., Prasad, V.R.B., Vinay, B.N. (2022). A Comprehensive Travel Recommendation System. In: Senjyu, T., Mahalle, P.N., Perumal, T., Joshi, A. (eds) ICT with Intelligent Applications. Smart Innovation, Systems and Technologies, vol 248. Springer, Singapore. https://doi.org/10.1007/978-981-16-4177-0_62
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DOI: https://doi.org/10.1007/978-981-16-4177-0_62
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