Context-aware recommender systems for social networks: review, challenges and opportunities
AB Suhaim, J Berri - IEEE Access, 2021 - ieeexplore.ieee.org
Context-aware recommender systems dedicated to online social networks experienced
noticeable growth in the last few years. This has led to more research being done in this …
noticeable growth in the last few years. This has led to more research being done in this …
A deep learning based trust-and tag-aware recommender system
Recommender systems are popular tools used in many applications, such as e-commerce, e-
learning, and social networks to help users select their desired items. Collaborative filtering …
learning, and social networks to help users select their desired items. Collaborative filtering …
A deep reinforcement learning based long-term recommender system
L Huang, M Fu, F Li, H Qu, Y Liu, W Chen - Knowledge-based systems, 2021 - Elsevier
Recommender systems aim to maximize the overall accuracy for long-term
recommendations. However, most of the existing recommendation models adopt a static …
recommendations. However, most of the existing recommendation models adopt a static …
A reliable deep representation learning to improve trust-aware recommendation systems
Deep neural networks have been extensively employed in many applications such as
natural language processing and computer vision. They have attracted a lot of attention in …
natural language processing and computer vision. They have attracted a lot of attention in …
Alleviating data sparsity problem in time-aware recommender systems using a reliable rating profile enrichment approach
Recommender systems use intelligent algorithms to learn a user's preferences and provide
them relevant suggestions. Lack of sufficient ratings–also known as data sparsity problem …
them relevant suggestions. Lack of sufficient ratings–also known as data sparsity problem …
X-ray image based COVID-19 detection using evolutionary deep learning approach
Radiological methodologies, such as chest x-rays and CT, are widely employed to help
diagnose and monitor COVID-19 disease. COVID-19 displays certain radiological patterns …
diagnose and monitor COVID-19 disease. COVID-19 displays certain radiological patterns …
A hybrid recommendation system based on profile expansion technique to alleviate cold start problem
Recommender systems are one of the information filtering tools which can be employed to
find interest items of users. Collaborative filtering is one of the recommendation methods to …
find interest items of users. Collaborative filtering is one of the recommendation methods to …
Toward point-of-interest recommendation systems: A critical review on deep-learning Approaches
In recent years, location-based social networks (LBSNs) that allow members to share their
location and provide related services, and point-of-interest (POIs) recommendations which …
location and provide related services, and point-of-interest (POIs) recommendations which …
An attention-based deep learning method for solving the cold-start and sparsity issues of recommender systems
Matrix Factorization is a successful approach for generating an effective recommender
system. However, most existing matrix factorization methods suffer from the sparsity and cold …
system. However, most existing matrix factorization methods suffer from the sparsity and cold …
Social trust-driven consensus reaching model for multiattribute group decision making: exploring social trust network completeness
With the development of social media, social networks (SNs) have gradually become the link
of information exchange between people. The social trust network (STN), a typical SN, is …
of information exchange between people. The social trust network (STN), a typical SN, is …