Personalized travel recommendation system : Hybrid model based on ratings and image analysis

Choosing a tourist place for vacation is very important, as a user spends a lot of money and efforts to choose a location wisely. To alleviate this effort, a travel recommendation system is introduced. However, the current recommendation system falls short of providing a perfect tourist location bec...

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Bibliographic Details
Main Authors: Bailke, Preeti, Gurav, Rohit, Suryawanshi, Sakshi, Narkhede, Parth, Hukare, Sejal, Patil, Sankalp
Format: Conference Proceeding
Language:English
Subjects:
Customization
Hybrid systems
Image analysis
Machine learning
Ratings
Recommender systems
Online Access:Get full text
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Summary:Choosing a tourist place for vacation is very important, as a user spends a lot of money and efforts to choose a location wisely. To alleviate this effort, a travel recommendation system is introduced. However, the current recommendation system falls short of providing a perfect tourist location because there are different types of users, each with their own preferences. So here, a user needs a personalized recommendation system. This paper focuses mainly on creating a machine-learning system that is a travel recommender system. It recommends a particular tourist place in two different ways. The first is based on ratings given by other users, and the second is based on previous images of places that users have previously visited. This machine learning model can be further linked to a website using Flask to make it easier for people to use it and search for their favorite destination. This system recommends a tourist attraction based on two factors: first, the ratings of each location given by other users, and second, the images users prefer. This paper mainly focuses on using SVD, LDA, and OpenCV.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0181493