A survey of community detection in complex networks using nonnegative matrix factorization
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 …
analysis. It aims to identify communities, represented as cohesive subgroups or clusters …
A weighted network community detection algorithm based on deep learning
S Li, L Jiang, X Wu, W Han, D Zhao, Z Wang - Applied Mathematics and …, 2021 - Elsevier
At present, community detection methods are mostly focused on the investigation at
unweighted networks. However, real-world networks are always complex, and unweighted …
unweighted networks. However, real-world networks are always complex, and unweighted …
An artificial-intelligence-enabled sustainable supply chain model for B2C E-commerce business in the international trade
B Qi, Y Shen, T Xu - Technological forecasting and social change, 2023 - Elsevier
This work aims to improve the efficiency of logistics distribution in the international trade
environment by optimizing the distribution path of the e-commerce supply chain model …
environment by optimizing the distribution path of the e-commerce supply chain model …
Dynamics of the COVID-19 contagion and mortality: Country factors, social media, and market response evidence from a global panel analysis
P Staszkiewicz, I Chomiak-Orsa, I Staszkiewicz - Ieee Access, 2020 - ieeexplore.ieee.org
This research asks how an epidemic affects human behaviour. Probably the COVID-19
contagion is the most adverse global public health, economic, social, and technological …
contagion is the most adverse global public health, economic, social, and technological …
Aspect-gated graph convolutional networks for aspect-based sentiment analysis
Q Lu, Z Zhu, G Zhang, S Kang, P Liu - Applied Intelligence, 2021 - Springer
Aspect-based sentiment analysis aims to predict the sentiment polarity of each specific
aspect term in a given sentence. However, the previous models ignore syntactical …
aspect term in a given sentence. However, the previous models ignore syntactical …
Modelling strong control measures for epidemic propagation with networks—A COVID-19 case study
M Small, D Cavanagh - IEEE access, 2020 - ieeexplore.ieee.org
We show that precise knowledge of epidemic transmission parameters is not required to
build an informative model of the spread of disease. We propose a detailed model of the …
build an informative model of the spread of disease. We propose a detailed model of the …
Blockchain-based event detection and trust verification using natural language processing and machine learning
Z Shahbazi, YC Byun - IEEE Access, 2021 - ieeexplore.ieee.org
Information sharing is one of the huge topics in social media platform regarding the daily
news related to events or disasters happens in nature or its human-made. The automatic …
news related to events or disasters happens in nature or its human-made. The automatic …
Time series clustering for TBM performance investigation using spatio-temporal complex networks
This paper proposes a network-enabled approach for analyzing time series data related to
tunnel boring machine (TBM) excavation behavior in the nature of high dimensionality and …
tunnel boring machine (TBM) excavation behavior in the nature of high dimensionality and …
Trust propagation and trust network evaluation in social networks based on uncertainty theory
Y Xu, Z Gong, JYL Forrest, E Herrera-Viedma - Knowledge-Based Systems, 2021 - Elsevier
Uncertainty distributions can help resolve the difficult problem of measuring subjective
uncertainty within a trust relationship. This paper studies trust propagation and trust network …
uncertainty within a trust relationship. This paper studies trust propagation and trust network …
Adaptive KNN and graph-based auto-weighted multi-view consensus spectral learning
Z Jiang, X Liu - Information Sciences, 2022 - Elsevier
The multi-view learning is a fundamental problem in the multimedia analysis. However, most
existing multi-view learning methods need to calculate a similarity matrix for each view. This …
existing multi-view learning methods need to calculate a similarity matrix for each view. This …