Blending Tradition with Technology: Saving TULUNAD Art through Machine Learning

Art’s remarkable ability to convey complex ideas with simplicity is a global phenomenon, yet some art forms struggle for recognition due to limited exposure or artists’ financial constraints. Bridging the gap between traditional art and modern society is crucial, and in the culturally rich TULUNADU region of Karnataka, this connection has been weak. This paper introduces a platform with an innovative recommendation engine to address this issue. It empowers patrons to explore artists’ work, make purchases, and engage directly with the creators. Using machine learning, the system tailors recommendations based on individual preferences. This platform is a product of advanced machine learning and web development tools, providing artists with analytics to refine their creative and promotional efforts. The proposed model boasts a 32% novelty rate and an impressive 99% diversity score, making it a valuable tool for marketing and recommending similar arts or products.