Deep learning-based collaborative filtering recommender systems: A comprehensive and systematic review
Nowadays, the volume of online information is growing and it is difficult to find the required
information. Effective strategies such as recommender systems are required to overcome …
information. Effective strategies such as recommender systems are required to overcome …
Facilitating radar-based gesture recognition with self-supervised learning
With deep learning, millimeter-wave radar-based gesture recognition applications have
achieved satisfactory results. However, most existing approaches highly rely on highquality …
achieved satisfactory results. However, most existing approaches highly rely on highquality …
Deep Learning-Based Recommendation System: Systematic Review and Classification
In recent years, recommendation systems have become essential for businesses to enhance
customer satisfaction and generate revenue in various domains, such as e-commerce and …
customer satisfaction and generate revenue in various domains, such as e-commerce and …
Implementation of a collaborative recommendation system based on multi-clustering
The study aims to present an architecture for a recommendation system based on user items
that are transformed into narrow categories. In particular, to identify the movies a user will …
that are transformed into narrow categories. In particular, to identify the movies a user will …
Customer Profiling Using Internet of Things Based Recommendations
The digital revolution caused major changes in the world because not only are people
increasingly connected, but companies are also turning more to the use of intelligent …
increasingly connected, but companies are also turning more to the use of intelligent …
Design of a music recommendation model on the basis of multilayer attention representation
W Lu - Scientific Programming, 2022 - Wiley Online Library
Current music recommendation systems can explore the general relationship between the
users and songs to recommend music to the users; however, they cannot distinguish the …
users and songs to recommend music to the users; however, they cannot distinguish the …
Non-pairwise Collaborative Filtering
On the users' interaction graph, neighbors have been widely explored in the embedding
function of collaborative filtering to address the sparsity issue. However, the embedding …
function of collaborative filtering to address the sparsity issue. However, the embedding …
Design and Implementation of Attention-based CR System in the Context of Big Data
Z Wang, Y Kuang, L Xin - IEEE Access, 2024 - ieeexplore.ieee.org
The recommendation accuracy of traditional product recommendation systems is insufficient.
Therefore, an improved deep factor decomposition machine algorithm combining adaptive …
Therefore, an improved deep factor decomposition machine algorithm combining adaptive …
Gated Hypergraph Neural Network for Scene-Aware Recommendation
To improve e-commercial recommender systems, researchers have never stopped exploring
the interactions between users and items. Unfortunately, most existing methods only explore …
the interactions between users and items. Unfortunately, most existing methods only explore …
A BiLSTM-attention-based point-of-interest recommendation algorithm
A Li, F Liu - Journal of Intelligent Systems, 2023 - degruyter.com
Aiming at the problem that users' check-in interest preferences in social networks have
complex time dependences, which leads to inaccurate point-of-interest (POI) …
complex time dependences, which leads to inaccurate point-of-interest (POI) …