Context and short term user intention aware hybrid session based recommendation system

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Abstract

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.

Original languageEnglish
Title of host publication2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications (INISTA)
EditorsPetia Koprinkova-Hristova, David Camacho, Tuly Yildirim, Lazaros Iliadis, Vincenzo Piuri
PublisherIEEE
Number of pages6
ISBN (Electronic)978-1-7281-1862-8, 978-1-7281-1861-1
ISBN (Print)978-1-7281-1863-5
DOIs
Publication statusPublished - 29 Jul 2019
Event2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications - Sofia, Bulgaria
Duration: 3 Jul 20195 Jul 2019

Conference

Conference2019 IEEE International Symposium on INnovations in Intelligent SysTems and Applications
Abbreviated titleINISTA 2019
Country/TerritoryBulgaria
CitySofia
Period3/07/195/07/19

Keywords

  • Context awareness
  • recommendation systems
  • session-based recommendation
  • short term user intention

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