Improved Session-based Recommender System by Context Awareness in e-Commerce Domain

Ramazan Esmeli, Mohamed Bader-El-Den, Hassana Abdullahi, David Henderson

2021

Abstract

Over the past two decades, there has been a rapid increase in the number of online sales. This has resulted in an increase in the data collected about the users’ behaviour which has aided the development of several novel Recommender System (RS) methods. One of the main problem in RS is the lack of ”explicit rating”; many customers do not rate the items they buy or view. However, the user behaviour (e.g. session duration, number of items, item duration view, etc.) during an online session could give an indication about what the user preferences ”implicit rating”. In this paper, we present a method to derive numerical implicit ratings from user browsing behaviour. Also, we examine the impact of using the derived numerical implicit ratings as context factors on some of the main RS methods, i.e. Factorisation Recommender and Item-Item Collaborative Filtering models. We evaluate the performance of the proposed framework on two large e-commerce datasets. The computational experiments show that in the absence of user explicit rating, the use of the user behaviour data to generate numerical implicit ratings could significantly improve the several RS methods.

Paper Citation

in Harvard Style

Esmeli R., Bader-El-Den M., Abdullahi H. and Henderson D. (2021). Improved Session-based Recommender System by Context Awareness in e-Commerce Domain. In Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - Volume 1: KDIR; ISBN 978-989-758-533-3, SciTePress, pages 37-47. DOI: 10.5220/0010656100003064

in Bibtex Style

@conference{kdir21,
author={Ramazan Esmeli and Mohamed Bader-El-Den and Hassana Abdullahi and David Henderson},
title={Improved Session-based Recommender System by Context Awareness in e-Commerce Domain},
booktitle={Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - Volume 1: KDIR},
year={2021},
pages={37-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010656100003064},
isbn={978-989-758-533-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2021) - Volume 1: KDIR
TI - Improved Session-based Recommender System by Context Awareness in e-Commerce Domain
SN - 978-989-758-533-3
AU - Esmeli R.
AU - Bader-El-Den M.
AU - Abdullahi H.
AU - Henderson D.
PY - 2021
SP - 37
EP - 47
DO - 10.5220/0010656100003064
PB - SciTePress