Context and short term user intention aware hybrid session based recommendation system
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Information overloading in e-commerce hinders the consumers' ability to make the right decisions. Customers visiting e-commerce websites can have specific goals in an individual session. However, using sessions that are based on the last item viewed or purchased is not enough to exploit the sessions specific intention or predict users' next actions in the sessions. In this paper, we proposed context and short term user intention aware (CSUI) framework which is based on item similarity collaborative filtering and Association Rule Session-based recommendation systems, the proposed model combines context factor of users' session and users' short term intentions. The developed model has been evaluated on two real-world datasets. Experimental results showed that using session context and users' short term intentions during the recommendation process could help in improving the accuracy of the next item prerlietion.
|Title of host publication||2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)|
|Editors||Petia Koprinkova-Hristova, David Camacho, Tuly Yildirim, Lazaros Iliadis, Vincenzo Piuri|
|Number of pages||6|
|ISBN (Electronic)||978-1-7281-1862-8, 978-1-7281-1861-1|
|Publication status||Published - 29 Jul 2019|
|Event||2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications - Sofia, Bulgaria|
Duration: 3 Jul 2019 → 5 Jul 2019
|Conference||2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications|
|Abbreviated title||INISTA 2019|
|Period||3/07/19 → 5/07/19|
- Ramazan_Paper_2_INISTA_2019_v2 (2)
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Accepted author manuscript (Post-print), 365 KB, PDF document