Intuitive Ecommerce System using Machine Learning

Ms. Sakshi K, Mr. Yash J.,Poornima K, Meghrani P.


Nowadays E-commerce is considered as a standard in industry providing customers with instant access to products or services at any given time without physical barriers and provides sellers to acquire a wide range of customers locally and globally. Customers are often overwhelmed by the plethora of options available on the net and spend significant time browsing the products that they wish to purchase. Hence an intuitive design is the need of the hour for all E-Commerce websites. This can be achieved by using the concept of “Machine Learning”. Machine Learning algorithms can help make sense of large amounts of data and provide actionable insights that retailers can use to make decisions later, or even in real-time. Also it helps the system make the user’s experience more personalized on the basis of his needs. This paper describes an effective system that would capture and make use of the user’s previous search and purchasing history so that personalized recommendations could be suggested to the user thereby making the system “intuitive”. General Terms: Database, Object oriented programming, Machine Learning.

Keywords :E-Commerce, Classification, Clustering, Collaborative Filtering, B2C.

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