Advanced Group Travel Recommendation System

Authors: Aman Pawar, Om Patil, Aditya Pardeshi, Arjun Singh

Country: India

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Abstract: In today's world of accessible and personalized travel, the demand for efficient and customized travel recommendations has grown significantly. This paper presents an advanced Travel Recommendation System that leverages data-driven insights to deliver personalized travel experiences. By integrating sophisticated algorithms and machine learning techniques, the system analyzes large datasets from multiple sources, such as user reviews, social media, and travel trends, to provide tailored suggestions. The system dynamically adapts to individual preferences, interests, and past behaviors, offering real-time recommendations that enhance user satisfaction. The approach demonstrates the potential of intelligent systems in shaping the future of personalized travel planning.

Keywords: Travel Recommendation System, Personalized Travel Experiences, Data-driven Insights, Machine Learning Techniques, User Preferences, Social Media Analysis, User Reviews, Travel Trends, Dynamic Adaptation, Real-time Recommendations, User Satisfaction, Intelligent Systems, Personalized Travel Planning, Algorithm Integration, Behavioral Analysis.

Paper Id: 232108

Published On: 2025-02-10

Published In: Volume 13, Issue 1, January-February 2025

Cite This: Advanced Group Travel Recommendation System - Aman Pawar, Om Patil, Aditya Pardeshi, Arjun Singh - IJIRMPS Volume 13, Issue 1, January-February 2025.

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