Abstract
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
Computer science
Scope (computer science)
E-commerce
Set (abstract data type)
World Wide Web
Data set
Data science
The Internet
Artificial intelligence
Web navigation
Web API
Subject Areas
Data Stream Mining Techniques
·Artificial Intelligence ·Physical Sciences
Web Data Mining and Analysis
·Information Systems ·Physical Sciences
Advanced Text Analysis Techniques
·Artificial Intelligence ·Physical Sciences
Citations by Year
2021: 2
2022: 2
OpenAlex SDG Match
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Industry, innovation and infrastructure 43%
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