Yayın: Prediction of Purchase Intention on the E-Commerce Clickstream Data
| dc.contributor.author | Gurbuz, Ahmet | |
| dc.contributor.author | Aktas, Mehmet S. | |
| dc.date.accessioned | 2026-06-27T14:20:52Z | |
| dc.date.issued | 2019 | |
| dc.description.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. | en |
| dc.description.uri | https://doi.org/10.1109/siu.2019.8806311 | |
| dc.identifier.doi | 10.1109/siu.2019.8806311 | |
| dc.identifier.isbn | 978-1-7281-1904-5 | |
| dc.identifier.issn | 2165-0608 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14981/59535 | |
| dc.identifier.wos | 000518994300046 | |
| dc.language.iso | tur | |
| dc.publisher | IEEE | |
| dc.relation.conference | 27th Signal Processing and Communications Applications Conference (SIU) | |
| dc.relation.ispartof | 2019 27TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | |
| dc.subject | Clickstream data | |
| dc.subject | Web usage mining | |
| dc.subject | Incremental clustering | |
| dc.subject | Anomaly Detection | |
| dc.subject | Engineering | |
| dc.subject | Telecommunications | |
| dc.title | Prediction of Purchase Intention on the E-Commerce Clickstream Data | |
| dc.type | Proceedings Paper | |
| dspace.entity.type | Publication | |
| local.import.source | WOS |