5 Years Impact Factor: 1.53
Author: G.Venkatesh, Vinjamuri Swathi, Addagudi Sandeep, Gullakadi Pranith Reddy
Abstract:
In this paper, we present a Decision Tree-based recommendation system designed to enhance tourist experiences by providing personalized recommendations for attractions and activities. The system leverages a decision tree algorithm to analyze tourists' preferences, historical data, and contextual information, such as location and time of year, to generate tailored suggestions. By incorporating features such as user profiles, past behavior, and popular destinations, the recommendation system aims to offer relevant and engaging options that align with individual interests. The effectiveness of the proposed system is evaluated through user feedback and comparison with existing recommendation methods, demonstrating its ability to deliver accurate and user-centric recommendations.
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