Content Based Apparel Recommendation for E-Commerce Stores
Utpal Chandra De, Shobhan Banerjee, Manas Kumar Rath, Tanmaya Swain, Tapaswini Samant · 2022 3rd International Conference for Emerging Technology (INCET) · 2022
Recommendation systems are extensively in use these days. These recommendations may be in the form of friend suggestions on Facebook, suggesting similar questions in Quora, or product suggestions on e-commerce sites, etc. Whenever we use an e-commerce website or app, we get to see product recommendations based on previous search history. Starting from OTT platforms like Prime and Netflix to general e-commerce sites like Flipkart and Amazon all of them use this feature so that the product search for the end-user becomes easier. It’s estimated that e-commerce platforms generate around 35% of their revenue just by these recommendation systems which run for their users. In this paper, we present a content-based recommendation system for women’s apparel where, given an apparel, the system generates other apparel to the users which are similar to the query apparel. We use various text-based techniques to retrieve the information from the product page based on the product image and its description.