A Click stream-Based Recommendation System with Machine Learning

Authors

Anurag Singh, Research scholar, Dr Subhadra Shaw, Assistant Professor of Computer Science
AKS University Satna, M.P, India.

Abstract

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.