Recommendation Model for Tourism Company TripAdvisor
This data set is populated by crawling TripAdvisor.com. Reviews on destinations in 10 categories mentioned across East Asia are considered. Each traveler rating is mapped as Excellent (4), Very Good (3), Average (2), Poor (1), and Terrible (0) and average rating is used against each category per user.
Task 1: Analysis we aim at comparing key clustering algorithms with the aim of finding an optimal option that can be adopted in tourism domain .
Task 2 : Recommendation of most higjly rated place.
Attribute 1 : Unique user id
Attribute 2 : Average user feedback on art galleries
Attribute 3 : Average user feedback on dance clubs
Attribute 4 : Average user feedback on juice bars
Attribute 5 : Average user feedback on restaurants
Attribute 6 : Average user feedback on museums
Attribute 7 : Average user feedback on resorts
Attribute 8 : Average user feedback on parks/picnic spots
Attribute 9 : Average user feedback on beaches
Attribute 10 : Average user feedback on theaters
Attribute 11 : Average user feedback on religious institutions
