Enhance the Quality of Recommendation System in E-Commerce Application

The recent trend of shopping has largely shifted towards online platforms. The future of online shopping to fulfil our needs looks promising since the internet is reaching to every corner of planet and various businesses are revolving around this. Online market provides customers a lot of options to choose from, this creates confusion among customers. To avoid this, platforms use something called recommendation systems which recommend products to customers based on their previous preferences and recent trends. Recent data also shows that enhancement in the recommendation system provides growth in business. So, recommendation system needs to be more accurate to fulfil both business and consumer needs. This paper discusses the enhancement of recommendations in E-Commerce platform using hybrid recommender system. Collaborative and Content based filtering has its own limitations, this paper provides a way to combine both and some other features-based filtering systems to get better results. Comparative study has also shown the better result for this method.