Traveller’s Guide: A Personalized Recommendation System For Tourists

Authors : Prof. Shrikant Kokate, Ashwini Gaikwad, Manisha Gutte, Pranita Patil, Kalyani Shinde

Volume/Issue : Volume 2 - 2017, Issue 11 - November

Google Scholar :

Scribd :

Thomson Reuters ResearcherID :

Recommender systems are currently being applied in many different domains. This paper focuses on their applicatons in tourism. Information about travel destination and their associated resources such as accommodations, restaueants, near by attaractions, is commonly searched by tourist in order to plan a trip or tourist may consult travel agencies for plan their trip.Tourist has to plan their trip according to agencies available packages. Each tourist’s interest, budget and need are not considered when trip is planned by travel agencies. There are generalized packages are offered by travel agencies and does not give freedom to tourist to choose their hotels, restaurants according to their choice, budget and need.To solve this problems we propose a system in which tourists will define their need , time, date, interest, hobbies then system provide recommendations like best places to travel which are nearer to his current location, cost of package, points according to season, schedule, hotels, transportation options based on his/her interest.

Keywords : Recommendation, KNN Clustering Algorithm, Apriori Classification Algorithm, Machine Learning, Supervised Machine Learning.


Paper Submission Last Date
31 - December - 2020

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.