[HTML][HTML] Auto-encoders in deep learning—a review with new perspectives
S Chen, W Guo - Mathematics, 2023 - mdpi.com
Deep learning, which is a subfield of machine learning, has opened a new era for the
development of neural networks. The auto-encoder is a key component of deep structure …
development of neural networks. The auto-encoder is a key component of deep structure …
A review of deep learning with special emphasis on architectures, applications and recent trends
Deep learning (DL) has solved a problem that a few years ago was thought to be intractable—
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
the automatic recognition of patterns in spatial and temporal data with an accuracy superior …
Effects of artificial Intelligence–Enabled personalized recommendations on learners' learning engagement, motivation, and outcomes in a flipped classroom
The flipped classroom approach is aimed at improving learning outcomes by promoting
learning motivation and engagement. Recommendation systems can also be used to …
learning motivation and engagement. Recommendation systems can also be used to …
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 …
Realizing an efficient IoMT-assisted patient diet recommendation system through machine learning model
C Iwendi, S Khan, JH Anajemba, AK Bashir… - IEEE access, 2020 - ieeexplore.ieee.org
Recent studies have shown that robust diets recommended to patients by Dietician or an
Artificial Intelligent automated medical diet based cloud system can increase longevity …
Artificial Intelligent automated medical diet based cloud system can increase longevity …
AI-based recommendation model for effective decision to maximise ROI
Healthcare researchers have recently concentrated their efforts on new medication
development methodologies that draw on existing pharmacological data. Even while drug …
development methodologies that draw on existing pharmacological data. Even while drug …
[HTML][HTML] Deep learning based semantic personalized recommendation system
The past decade has seen significant development in the number of personalized
recommendation applications on the World Wide Web. It aims to assist users to retrieve …
recommendation applications on the World Wide Web. It aims to assist users to retrieve …
[HTML][HTML] DeepReco: deep learning based health recommender system using collaborative filtering
In today's digital world healthcare is one core area of the medical domain. A healthcare
system is required to analyze a large amount of patient data which helps to derive insights …
system is required to analyze a large amount of patient data which helps to derive insights …
[HTML][HTML] Deep learning architecture for collaborative filtering recommender systems
J Bobadilla, S Alonso, A Hernando - Applied Sciences, 2020 - mdpi.com
This paper provides an innovative deep learning architecture to improve collaborative
filtering results in recommender systems. It exploits the potential of the reliability concept to …
filtering results in recommender systems. It exploits the potential of the reliability concept to …
Deep learning in citation recommendation models survey
The huge amount of research papers on the web makes finding a relevant manuscript a
difficult task. In recent years many models were introduced to support researchers by …
difficult task. In recent years many models were introduced to support researchers by …