Authors :
A Naga Jyothi; Giresh Raju Adimulam; Chandu Neelam; Janni Narasimha Gowud VNL; Raj Kumar Unnamatla; Karthikeya Tumpati
Volume/Issue :
Volume 10 - 2025, Issue 4 - April
Google Scholar :
https://tinyurl.com/2s3d8rd7
Scribd :
https://tinyurl.com/yvw8ud9j
DOI :
https://doi.org/10.38124/ijisrt/25apr515
Google Scholar
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 15 to 20 days to display the article.
Abstract :
The AI-Powered TRAVEL FINDER represents a groundbreaking innovation in the realm of travel technology,
specifically crafted to bridge the gap between solo traveller and like-minded individuals, thereby fostering enriching shared
travel experiences. Harnessing the capabilities of Artificial Intelligence (AI) and Machine Learning (ML), this platform
meticulously analyses an array of user preferences, including desired destinations, travel dates, budgetary constraints, and
personal interests, to generate highly personalized recommendations for travel companions. With a strong emphasis on
building a sense of community, the application ensures that solo travellers no longer need to embark on their journeys in
isolation, instead offering them opportunities to connect with others who share similar passions and travel goals. At its core,
the system employs sophisticated smart matching algorithms, such as collaborative filtering and clustering techniques, which
dynamically curate new travel groups or integrate users into existing ones based on overlapping interests, guaranteeing
harmonious and enjoyable group dynamics throughout the trip. By transforming the often-solitary nature of solo travel into
a collaborative and socially engaging adventure, the AI-Powered Travel Finder addresses key challenges such as isolation,
while simultaneously promoting cultural exchange and fostering deep, meaningful connections among travellers. Whether
the purpose of the journey is leisure, adventure, or even business, this platform redefines the travel landscape, ensuring that
no one has to experience the wonders of exploration alone. Through its innovative approach, the AI-Powered Travel Finder
not only enhances the practicality of travel planning but also enriches the emotional and social dimensions of every journey,
making it a vital tool for modern travellers seeking both convenience and companionship.
References :
- Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). "Latent Dirichlet Allocation." Journal of Machine Learning Research, 3, 993-1022.
- Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to Information Retrieval. Cambridge University Press.
- Van Laarhoven, T., & Marchiori, E. (2014). "Gaussian Similarity for Spectral Clustering." Pattern Recognition Letters, 40, 1-6.
- Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson Education.
- Cheng, C., Yang, H., Lyu, M. R., & King, I. (2013). "Where You Like to Go Next: Successive Point-of-Interest Recommendation." Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI), 2605-2611.
- Crew-AI Documentation. (2024). "Automating Dynamic Decision-Making with AI Agents." Retrieved from: https://github.com/jerryjliu/crewAI.
- Google Cloud AI Services. (2023). "Machine Learning for Personalized Recommendations." Retrieved from: https://cloud.google.com/ai.
- OpenAI. (2023). "Natural Language Processing and AI-driven Travel Assistance." Retrieved from: https://openai.com/research.
- Pellungrini, R., & Ruggieri, S. (2021). "Privacy-Preserving AI in Recommender Systems." ACM Transactions on Intelligent Systems and Technology, 12(3), 32.
- Sharma, R., & Gupta, A. (2021). "Blockchain for Secure Travel Transactions." International Conference on Emerging Technologies in Computing, 1-10.
- IEEE Xplore Digital Library. (2024). "Advancements in AI-Powered Trip Planning." Retrieved from: https://ieeexplore.ieee.org.
The AI-Powered TRAVEL FINDER represents a groundbreaking innovation in the realm of travel technology,
specifically crafted to bridge the gap between solo traveller and like-minded individuals, thereby fostering enriching shared
travel experiences. Harnessing the capabilities of Artificial Intelligence (AI) and Machine Learning (ML), this platform
meticulously analyses an array of user preferences, including desired destinations, travel dates, budgetary constraints, and
personal interests, to generate highly personalized recommendations for travel companions. With a strong emphasis on
building a sense of community, the application ensures that solo travellers no longer need to embark on their journeys in
isolation, instead offering them opportunities to connect with others who share similar passions and travel goals. At its core,
the system employs sophisticated smart matching algorithms, such as collaborative filtering and clustering techniques, which
dynamically curate new travel groups or integrate users into existing ones based on overlapping interests, guaranteeing
harmonious and enjoyable group dynamics throughout the trip. By transforming the often-solitary nature of solo travel into
a collaborative and socially engaging adventure, the AI-Powered Travel Finder addresses key challenges such as isolation,
while simultaneously promoting cultural exchange and fostering deep, meaningful connections among travellers. Whether
the purpose of the journey is leisure, adventure, or even business, this platform redefines the travel landscape, ensuring that
no one has to experience the wonders of exploration alone. Through its innovative approach, the AI-Powered Travel Finder
not only enhances the practicality of travel planning but also enriches the emotional and social dimensions of every journey,
making it a vital tool for modern travellers seeking both convenience and companionship.