AN EFFICIENT APPROACH OF TRAVEL RECOMMENDATION MODEL FROM HIGH DIMENSIONAL DATABASES

The Paper discusses Recommendation system to give high preferred tourist locations by analysing social networks users shared information the objectives of this study: To utilize the publicly available data from the social networking websites for understanding and analyzing the mobility behaviors of the users from different parts of the world. To present novel system architecture that is capable of addressing dynamic queries for semantically meaningful and personalized tourist location recommendations using geotagged social media. More specifically, the queries may include any or all of the contexts. To recognize the mobility patterns among the users from their travelling routines and covered distances. And furthermore, recommend the places to users based on their history of geo tagging and their travels without affecting their privacy.