A comprehensive survey on trustworthy recommender systems
As one of the most successful AI-powered applications, recommender systems aim to help
people make appropriate decisions in an effective and efficient way, by providing …
people make appropriate decisions in an effective and efficient way, by providing …
Exploring the Landscape of Hybrid Recommendation Systems in E-Commerce: A Systematic Literature Review
This article presents a systematic literature review on hybrid recommendation systems
(HRS) in the e-commerce sector, a field characterized by constant innovation and rapid …
(HRS) in the e-commerce sector, a field characterized by constant innovation and rapid …
Predicting popularity of online products via collective recommendations
Predicting the future popularity of commodities has always been a significant issue in
information filtering research. Existing methods predominantly rely on the historical …
information filtering research. Existing methods predominantly rely on the historical …
User-centric evaluation of recommender systems: a literature review
K Nanath, M Ahmed - International Journal of Business …, 2023 - inderscienceonline.com
Recommender systems have seen a rapid rise of application in various industries, with
several services now being implemented online. Over the years, various authors have been …
several services now being implemented online. Over the years, various authors have been …
An in-depth analysis of robustness and accuracy of recommendation systems
H Ma, C Wang, Y Zhao, L Wang, X Cao… - … Conference on Data …, 2023 - ieeexplore.ieee.org
Recommender systems are extensively deployed in e-commerce, social networks, app
markets, etc., as it facilitates the human decision-making process due to its capability in …
markets, etc., as it facilitates the human decision-making process due to its capability in …
Exploratory study of machine learning algorithms in recommender systems
Recommender systems are widely used by various companies today to help create
personalized experiences for users or consumers. These systems incorporate a lot of …
personalized experiences for users or consumers. These systems incorporate a lot of …
Modeling and Optimization of Discrete Evolutionary Systems of İnformation Security Management in a Random Environment
A method for studying the stability of zero solutions of a system of nonlinear difference
equations depending on the semi-Markov chain is proposed. The essence of the proposed …
equations depending on the semi-Markov chain is proposed. The essence of the proposed …
[PDF][PDF] Exploring the Landscape of Hybrid Recommendation Systems in E-Commerce: A Systematic
H LÖWENADLER - 2024 - diva-portal.org
This article presents a systematic literature review on hybrid recommendation systems
(HRS) in the e-commerce sector, a field characterized by constant innovation and rapid …
(HRS) in the e-commerce sector, a field characterized by constant innovation and rapid …
High Order Profile Expansion to tackle the new user problem on recommender systems
Collaborative Filtering algorithms provide users with recommendations based on their
opinions, that is, on the ratings given by the user for some items. They are the most popular …
opinions, that is, on the ratings given by the user for some items. They are the most popular …
Model-Based Learning to Augment Collaborative Filtering: Prediction and Evaluation
A Althbiti - 2021 - search.proquest.com
Collaborative filtering (CF) is a novel statistical technique developed to retrieve useful
information and to generate predictions based on provided data from users. It is …
information and to generate predictions based on provided data from users. It is …