[HTML][HTML] An analyses of the effect of using contextual and loyalty features on early purchase prediction of shoppers in e-commerce domain

R Esmeli, M Bader-El-Den, H Abdullahi - Journal of Business Research, 2022 - Elsevier
Online sales have been growing rapidly in recent years. With the growing competition,
online retailers have been keen to increase the effectiveness of their e-commerce platforms …

Using Word2Vec recommendation for improved purchase prediction

R Esmeli, M Bader-El-Den… - 2020 International Joint …, 2020 - ieeexplore.ieee.org
Purchase prediction can help e-commerce planners plan their stock and personalised offers.
Word2Vec is a well-known method to explore word relations in sentences for sentiment …

Miko: Multimodal Intention Knowledge Distillation from Large Language Models for Social-Media Commonsense Discovery

F Lu, W Wang, Y Luo, Z Zhu, Q Sun, B Xu… - Proceedings of the …, 2024 - dl.acm.org
Social media has become ubiquitous for connecting with others, staying updated with news,
expressing opinions, and finding entertainment. However, understanding the intention …

Implicit feedback awareness for session based recommendation in e-commerce

R Esmeli, M Bader-El-Den, H Abdullahi… - SN Computer …, 2023 - Springer
Abstract Information overload is a challenge in e-commerce platforms. E-shoppers may have
difficulty selecting the best product from the available options. Recommender systems (RS) …

How should Bank Syariah Indonesia respond to cyber-attacks? Churn, sentiments, and emotions analysis with machine learning

YP Timur, AA Ridlwan, K Fikriyah… - Journal of Islamic …, 2024 - journal.uii.ac.id
Objectives The objective of this study is to investigate the public's response to cyberattacks
on Bank Syariah Indonesia, focusing on identifying key topics, analyzing sentiments and …

Session similarity based approach for alleviating cold-start session problem in e-commerce for Top-N recommendations

R Esmeli, M Bader-El-Den… - 12th International Joint …, 2020 - researchportal.port.ac.uk
Cold-start problem is one of the main challenges for the recommender systems. There are
many methods developed for traditional recommender systems to alleviate the drawback of …

SMONE: A Session-based Recommendation Model Based on Neighbor Sessions with Similar Probabilistic Intentions

B Jia, J Cao, S Qian, N Zhu, X Dong, L Zhang… - ACM Transactions on …, 2023 - dl.acm.org
A session-based recommendation system (SRS) tries to predict the next possible choice of
anonymous users. In recent years, graph neural network (GNN) models have been …

An Evaluation of Core Factors of Predictive Analytics in Influencing Purchase Decision of the Consumers in E-business

J Masih, M Mathur, A Bhagwat, S Mishra… - … Intelligence, Internet of …, 2023 - Springer
Business intelligence and predictive analytics skills is a significant growth driver in e-
commerce operations. These capabilities assist to enhance vendor sales and attract …

Improving session-based recommendation adopting linear regression-based re-ranking

R Esmeli, M Bader-El-Den, H Abdullahi… - … Joint Conference on …, 2020 - ieeexplore.ieee.org
Due to the increase in the importance of giving real-time recommendation to e-commerce
users, session-based recommender systems become more popular. Session-based …

Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms

R Esmeli, A Mohasseb… - 12th International Joint …, 2020 - researchportal.port.ac.uk
Predicting future consumer browsing and purchase behaviour has become crucial to many
marketing platforms. Consumer purchase intention is one of the main inputs used as a …