An Extensive Analysis of Product Suggestion Systems

In modern times, the Internet has become a package of parts and everyday life. During the Covid 19 pandemic, all sectors range from food delivery, e-commerce, education, learning, health services and more. With lighter product selection and wider accessibility, e-commerce gains popularity at a faster pace. In it, consumers are exposed to a variety of options for the products of their interest. It is a major challenge for users to select high quality products at the right cost. Product recommendation systems are used for this purpose and support users in their decisions to select the right product. Product Recommendations System analyzes product tests and provides recommendations for the product. Based on previous reviews, this recommendation may be positive or negative. A comprehensive study of recommendation systems provides the work presented here. It covers a variety of aspects of the various methods, ranging from content-based filtering methods to hybrid filtering methods used in current recommended systems. The current study shows the impact of recommendation systems on e-commerce businesses Keywords:E-commerce, Quality product, decision making, Recommendation, Content-based filtering, collaborative base filter, hybrid filtering.