Sherpa: Implementing a Hybrid Recommendation System for Next-Gen Tourist Experience

Inam Ullah Khan,Abdur Rahman, Muhammad Awais Khan,Dr.Madiha Sher,Dr. Yasir Saleem
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Inam Ullah Khan,Abdur Rahman, Muhammad Awais Khan,Dr.Madiha Sher,Dr. Yasir Saleem: Department of Computer Systems Engineering, University of Engineering and Technology Peshawar Pakistan

International Journal of Innovations in Science & Technology, 2024, vol. 6, issue 5, 37-42

Abstract: In the digital era, Sherpa revolutionizes personalized tourism with an AI-driven recommendation system, fostering meaningful connections between travelers and local guides. This study explores Sherpa's integration of collaborative and content-based filtering—specifically, singular value decomposition (SVD) and cosine similarity—to tailor travel experiences uniquely. Our methodology includes a detailed examination of Sherpa's algorithm and its implementation within a cross-platform, MERN Stack-powered backend. We assess the system's efficacy in aligning recommendations with individual user preferences, based on quantitative user feedback and engagement metrics. Initial results demonstrate a significant improvement in personalized experience satisfaction. The paper concludes that Sherpa's innovative approach not only enhances the quality of travel recommendations but also sets a new standard for interactive and adaptive tourism platforms. Through continuous algorithmic refinement, Sherpa is positioned to lead a transformative shift in how travelers explore new destinations, offering not just journeys, but transformative experiences.

Keywords: Artificial Intelligence; Digital Tourism; Collaborative Filtering; Content-Based Filtering; Hybrid Recommender System; Singular Value Decomposition; Cosine Similarity Matrix. (search for similar items in EconPapers)
Date: 2024
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