CoursePlate: Personalized Restaurant Recommendation System | IJCT Volume 12 – Issue 6 | IJCT-V12I6P20
International Journal of Computer Techniques
ISSN 2394-2231
Author
Donggwan Kwon, Sunghoon Jeon, Seungmin Lee, Jaeyoung Yeom, Seungjae Lee
Abstract
This paper presents a personalized restaurant recommendation system, CoursePlate, leveraging open-source tools and APIs, including React Native, Expo, MongoDB, and Naver Maps API. The system provides real-time personalized food recommendations based on user preferences and location, offering an intuitive user interface and seamless navigation experience. The integration of Naver Maps API allows for easy location-based services, while the receipt verification system ensures the credibility of user reviews, preventing fraudulent ones and improving trust in the platform.
Keywords
Open Source, Restaurant Recommendation, Naver Maps API, React Native, MongoDB
Conclusion
The CoursePlate application, powered by open-source tools like React Native and Naver Maps API, offers a user-friendly and efficient platform for food exploration. The integration of personalized recommendations, real-time navigation, and reliable review systems has the potential to significantly enhance the dining experience. Future work will involve expanding the system’s capabilities to include more dynamic data sources and further improve recommendation accuracy.
References
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How to Cite This Paper
Donggwan Kwon, Sunghoon Jeon, Seungmin Lee, Jaeyoung Yeom, Seungjae Lee (2025). CoursePlate: Personalized Restaurant Recommendation System. International Journal of Computer Techniques, 12(6). ISSN: 2394-2231.
