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@article{188984,
        author = {Anushka Sadashiv Lohakare and Prerana Surykant Bhondave and Riya Sunil Pipriye and Sakshi Devidas Satpute and Poonam Chavhan},
        title = {Stylesphere – A Fashion Recommendation System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {7},
        pages = {5061-5065},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=188984},
        abstract = {With the rapid growth of online shopping, users often face challenges such as difficulty in finding personalized fashion products, inconsistent styling guidance, and lack of unified platforms offering tailored recommendations. To address these problems, Stylesphere is developed as a smart fashion recommendation and styling system designed to enhance user experience and assist shoppers in making confident style choices. Based on the idea that personalized fashion filtering can significantly improve product discovery, we propose an AI-aided solution built using modern web technologies capable of delivering dynamic styling suggestions, skin-tone based product filtering, trend-based recommendations, and user-specific lookbooks. The objective of Stylesphere is to streamline product browsing, improve buyer satisfaction, support businesses in presenting curated fashion collections, and reduce user confusion caused by overwhelming product variety. To achieve these goals, an intelligent system capable of understanding user preferences, traits, and fashion behaviour is required.},
        keywords = {Fashion, Recommendation System, AI, Skin-tone Analysis, Web Application, Personal Styling, Client-Server Architecture.},
        month = {December},
        }