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Mobile aplication for personalized coffee taste recommendations
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Keywords
Recommender systems ; Adaptive systems ; Personalization ; Android ; Firebase ; User experience ; Specialty coffeeAbstract
This thesis focuses on the problem of information overload faced by consumers in the specialty coffee market. To address this challenge, "YourCoffeeGuide" was designed and developed, an intelligent mobile application for Android devices that acts as a personalized taste recommendation guide. The application utilizes a hybrid and adaptive algorithm, which initially generates recommendations based on the user's stated preferences and subsequently evolves by learning from their ratings to offer increasingly accurate suggestions. The implementation was carried out as a native application in Java using Android Studio, while the system's architecture is based on the Client-Server model, leveraging the Google Firebase platform for user authentication and real-time data storage. The final result is a functional prototype that demonstrates the effectiveness of the proposed solution, transforming the complex process of coffee selection into a simple and enjoyable discovery experience.
Department
Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα ΠληροφορικήςNumber of pages
75Language
GreekCollections
Except where otherwise noted, this item's license is described as
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα
Αναφορά Δημιουργού-Μη Εμπορική Χρήση-Όχι Παράγωγα Έργα 3.0 Ελλάδα