Image-Based Product Recommendations Using Market Basket Analysis

Most online shopping search engines are still largely depending on the knowledge base and use keyword matching as their search strategy to find the most likely product that consumers want to buy. This is inefficient in a way that the description of products can vary a lot from the seller's side to the buyer's side. The proposed interactive product recommendation method considers not only the product history of the customer but also the linkage between the same products bought by other customers to recommend new products. The image was provided as an input to the model, and Convolutional Neural Networks has been used to classify the image, and recommendations are generated using market basket analysis.