A Click stream-Based Recommendation System with Machine Learning

With the increment in the utilization of the Internet, the pace of increment of social networks is getting ubiquitous in recent years. Click-stream data is an important source to enhance user experience and pursue business objectives in e-commerce. The paper uses click-stream data to predict online shopping behavior and target marketing interventions. The paper represents a study of various existing recommendation systems and proposes a recommendation system that utilizes different Machine Learning procedures which results in showing that Random Forest Classifier (RFC) gives the most noteworthy expectation accuracy when contrasted with different procedures.