A survey of community detection in complex networks using nonnegative matrix factorization

C He, X Fei, Q Cheng, H Li, Z Hu… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Community detection is one of the popular research topics in the field of complex networks
analysis. It aims to identify communities, represented as cohesive subgroups or clusters …

An overview of recommendation techniques and their applications in healthcare

W Yue, Z Wang, J Zhang, X Liu - IEEE/CAA Journal of …, 2021 - ieeexplore.ieee.org
With the increasing amount of information on the internet, recommendation system (RS) has
been utilized in a variety of fields as an efficient tool to overcome information overload. In …

Fast and accurate non-negative latent factor analysis of high-dimensional and sparse matrices in recommender systems

X Luo, Y Zhou, Z Liu, MC Zhou - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
A fast non-negative latent factor (FNLF) model for a high-dimensional and sparse (HiDS)
matrix adopts a Single Latent Factor-dependent, Non-negative, Multiplicative and …

A survey of collaborative filtering-based recommender systems: From traditional methods to hybrid methods based on social networks

R Chen, Q Hua, YS Chang, B Wang, L Zhang… - IEEE …, 2018 - ieeexplore.ieee.org
In the era of big data, recommender system (RS) has become an effective information
filtering tool that alleviates information overload for Web users. Collaborative filtering (CF) …

Temporal pattern-aware QoS prediction via biased non-negative latent factorization of tensors

X Luo, H Wu, H Yuan, MC Zhou - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Quality-of-service (QoS) data vary over time, making it vital to capture the temporal patterns
hidden in such dynamic data for predicting missing ones with high accuracy. However …

[HTML][HTML] A survey on fairness-aware recommender systems

D **, L Wang, H Zhang, Y Zheng, W Ding, F **a… - Information …, 2023 - Elsevier
As information filtering services, recommender systems have extremely enriched our daily
life by providing personalized suggestions and facilitating people in decision-making, which …

Elliot: A comprehensive and rigorous framework for reproducible recommender systems evaluation

VW Anelli, A Bellogín, A Ferrara, D Malitesta… - Proceedings of the 44th …, 2021 - dl.acm.org
Recommender Systems have shown to be an effective way to alleviate the over-choice
problem and provide accurate and tailored recommendations. However, the impressive …

Diversified regularization enhanced training for effective manipulator calibration

Z Li, S Li, OO Bamasag, A Alhothali… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recently, robot arms have become an irreplaceable production tool, which play an important
role in the industrial production. It is necessary to ensure the absolute positioning accuracy …

Robust latent factor analysis for precise representation of high-dimensional and sparse data

D Wu, X Luo - IEEE/CAA Journal of Automatica Sinica, 2020 - ieeexplore.ieee.org
High-dimensional and sparse (HiDS) matrices commonly arise in various industrial
applications, eg, recommender systems (RSs), social networks, and wireless sensor …

Movie recommender system using k-means clustering and k-nearest neighbor

R Ahuja, A Solanki, A Nayyar - 2019 9th International …, 2019 - ieeexplore.ieee.org
In the field of Artificial Intelligence Machine learning provides the automatic systems which
learn and improve itself from experience without being explicitly programmed. In this …