A Web-Based Smart Outfit Recommendation System Using Node.js, Express.js and MySQL for Dynamic Fashion Recommendations

This research study proposes a Smart Outfit Recommendation System designed to give users personalized fashion suggestions based on their body shape, gender, skin tone, and the occasion. Using advanced technology, the system makes picking clothes easier and less reliant on traditional, costly methods that require a lot of work from fashion designers. Users interact with the system through an intuitive interface where they can enter their style preferences, occasion, and personal traits. Based on these details, the system searches a large clothing database to find the best outfit options. The backend of the platform is built using Node.js and Express.js, with HTML, CSS, and JavaScript used for the frontend, offering a smooth experience for users. The clothing database is managed with MySQL, ensuring quick and accurate recommendations. A standout feature is the integration with e-commerce platforms, enabling users to buy suggested items with just a few clicks. Besides making shopping easier, the system keeps up with fashion trends, so recommendations are always current. By streamlining the outfit selection process, it helps reduce decision fatigue, saving users time and improving their shopping experience.