A novel deep learning-based collaborative filtering model for recommendation system
The collaborative filtering (CF) based models are capable of grasping the interaction or
correlation of users and items under consideration. However, existing CF-based methods …
correlation of users and items under consideration. However, existing CF-based methods …
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 …
An α–β-divergence-generalized recommender for highly accurate predictions of missing user preferences
To quantify user–item preferences, a recommender system (RS) commonly adopts a high-
dimensional and sparse (HiDS) matrix. Such a matrix can be represented by a non-negative …
dimensional and sparse (HiDS) matrix. Such a matrix can be represented by a non-negative …
Latent factor-based recommenders relying on extended stochastic gradient descent algorithms
High-dimensional and sparse (HiDS) matrices generated by recommender systems contain
rich knowledge regarding various desired patterns like users' potential preferences and …
rich knowledge regarding various desired patterns like users' potential preferences and …
Recommendation based trust model with an effective defence scheme for MANETs
The reliability of delivering packets through multi-hop intermediate nodes is a significant
issue in the mobile ad hoc networks (MANETs). The distributed mobile nodes establish …
issue in the mobile ad hoc networks (MANETs). The distributed mobile nodes establish …
Evaluation of hotel brand competitiveness based on hotel features ratings
Understanding the competitiveness of hotel brands is important for hotel managers to shape
their brands and initiate effective marketing strategies and business developments …
their brands and initiate effective marketing strategies and business developments …
Optimized recommendations by user profiling using apriori algorithm
Collaborative filtering has been the most straightforward and most preferable approach in
the recommender systems. This technique recommends an item to a target user from the …
the recommender systems. This technique recommends an item to a target user from the …
Deep matrix factorization for trust-aware recommendation in social networks
Recent years have witnessed remarkable information overload in online social networks,
and social network based approaches for recommender systems have been widely studied …
and social network based approaches for recommender systems have been widely studied …
A large-scale web QoS prediction scheme for the Industrial Internet of Things based on a kernel machine learning algorithm
X Luo, J Liu, D Zhang, X Chang - Computer Networks, 2016 - Elsevier
Cloud computing plays an essential role in enabling practical applications based on the
Industrial Internet of Things (IIoT). Hence, the quality of these services directly impacts the …
Industrial Internet of Things (IIoT). Hence, the quality of these services directly impacts the …
A survey on data mining techniques in recommender systems
Recommender systems have been regarded as gaining a more significant role with the
emergence of the first research article on collaborative filtering (CF) in the mid-1990s. CF …
emergence of the first research article on collaborative filtering (CF) in the mid-1990s. CF …