[HTML][HTML] Blockchain-based recommender systems: Applications, challenges and future opportunities
Recommender systems have been widely used in different application domains including
energy-preservation, e-commerce, healthcare, social media, etc. Such applications require …
energy-preservation, e-commerce, healthcare, social media, etc. Such applications require …
A comparative review on multi-modal sensors fusion based on deep learning
The wide deployment of multi-modal sensors in various areas generates vast amounts of
data with characteristics of high volume, wide variety, and high integrity. However, traditional …
data with characteristics of high volume, wide variety, and high integrity. However, traditional …
" Guidelines" for collaborative learning in 21st century education at Madrasah Tsanawiyah
In the 21st century, as globalization expands, education must be able to defend its culture
and civilization against foreign culture and comprehension. As a multicultural nation whose …
and civilization against foreign culture and comprehension. As a multicultural nation whose …
RETRACTED ARTICLE: Customer centric hybrid recommendation system for E-Commerce applications by integrating hybrid sentiment analysis
Internet applications such as Online Social Networking and Electronic commerce are
becoming incredibly common, resulting in more content being available. Recommender …
becoming incredibly common, resulting in more content being available. Recommender …
Making sense of spatio-temporal preserving representations for EEG-based human intention recognition
Brain-computer interface (BCI) is a system empowering humans to communicate with or
control the outside world with exclusively brain intentions. Electroencephalography (EEG) …
control the outside world with exclusively brain intentions. Electroencephalography (EEG) …
Deep learning techniques for recommender systems based on collaborative filtering
Abstract In the Big Data Era, recommender systems perform a fundamental role in data
management and information filtering. In this context, Collaborative Filtering (CF) persists as …
management and information filtering. In this context, Collaborative Filtering (CF) persists as …
A novel deep multi-criteria collaborative filtering model for recommendation system
Recommender systems have been in existence everywhere with most of them using single
ratings in prediction. However, multi-criteria predictions have been proved to be more …
ratings in prediction. However, multi-criteria predictions have been proved to be more …
An efficient group recommendation model with multiattention-based neural networks
Group recommendation research has recently received much attention in a recommender
system community. Currently, several deep-learning-based methods are used in group …
system community. Currently, several deep-learning-based methods are used in group …
A deep learning based algorithm for multi-criteria recommender systems
Q Shambour - Knowledge-based systems, 2021 - Elsevier
Recommender systems have become exceptionally widespread in recent years to deal with
the information overload problem by providing personalized recommendations. Multi-criteria …
the information overload problem by providing personalized recommendations. Multi-criteria …
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 …