• D Kaja Hussain
• V N Nevedha
• A Karthik Raju
• C Vinod Kumar
• Y Meghana

Recommender systems that work well can help customers find things they like and help businesses make more money. However, user decision-making is quite intricate and is impacted by both individual tastes and the particular features of an item. Because the characteristics of items that influence user decisions differ greatly between categories (clothing vs. office products, for example), traditional collaborative filtering approaches that only simulate user-item interactions sometimes produce suggestions that are not suitable. In order to increase the quality of recommendations, this work focuses on fine-grained modeling of product features. In particular, a product's features are separated into its functional and visual elements, or its functionality and visual appeal, respectively. The realization is that whereas functional features are more important in visually non aware domains (like office items), visual attributes are more important in visually conscious domains (like clothes). The Visual and Functional Probabilistic Matrix Factorization (VFPMF), a unique probabilistic model, is offered as a solution to this problem. This approach estimates consumer preferences for items by combining both functional and visual aspects. Parameter learning from implicit feedback presents efficiency issues when using such an expressive model. A computationally effective learning technique based on alternating least squares is developed in order to get around this technological obstacle. Additionally, an online update process is offered, which clarifies how to modify the approach for real-world recommendation scenarios where data is continually flowing in.

Product, Recommendations, Feedback, Data, Clothing

"Incorporating Visual Appearance and Utility Features for Enhanced Product Recommendations", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 5, page no.p48-p52, May-2024, Available :http://www.jetir.org/papers/JETIR2405G09.pdf

"Incorporating Visual Appearance and Utility Features for Enhanced Product Recommendations", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 5, page no. ppp48-p52, May-2024, Available at : http://www.jetir.org/papers/JETIR2405G09.pdf