E Commerce Recommendation

E-commerce recommendation systems aim to personalize online shopping experiences by suggesting relevant products to individual users. Current research heavily focuses on incorporating rich textual information from product descriptions and user reviews, leveraging techniques like transformer-based neural networks and large language models to improve recommendation accuracy and relevance. These advancements are driven by the need to overcome limitations of traditional methods, such as sparsity in user data and the inability to fully capture user intent, ultimately leading to increased user engagement and sales for e-commerce platforms. Furthermore, incorporating post-serving contextual information and addressing user fatigue are emerging areas of focus.