Prediction of Purchase Intention on the E-Commerce Clickstream Data - Gurbuz, Ahmet; Aktas, Mehmet S. (IEEE, 2019)
Every day millions of customers do shopping through e-commerce web sites around the world. Huge amounts of click stream data are generated from customers' use of e-commerce websites. Learning the behavior of users from click data and estimating the intention to buy has become an important need. Within the scope of this research, a methodology is proposed on the estimation of the purchase intention before finalizing the sessions of the customers. The proposed methodology was tested by the ACM RecSys Symposium on e-commerce data set published in 2015 and it was found that successful results could be obtained.
Keywords: Clickstream data; Web usage mining; Incremental clustering; Anomaly Detection; Engineering; Telecommunications