Deep Learning-Based Product Recommendation System

Abstract

Recommendations based on visual resemblance play a significant role in e- commerce platforms since they assist customers in selecting the desired items more quickly. Despite its huge potential, the number of recommendation systems on this topic is limited. An effective recommendation system is necessary to properly sort, order, and communicate relevant product material or in- formation to users. Here in our research, we presented an efficient E- commerce similar product network model for visually similar recommendations. To achieve our objective, we have performed image feature extraction and generating embeddings(Denoising-Autoencoder) using deep learning techniques and built an Index tree using the K-Nearest Neighbour classification(KNN) algorithm. Further, we have fetched top-N the near similar items using a distance measure. We have benchmarked our model in terms of accuracy and error rate, and it’s a new approach with 93% accuracy.