Big graph classification frameworks based on Extreme Learning Machine
Sign Up to like & getrecommendations! Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.11.035
Abstract: Abstract Graph data analysis is a hot topic in recent research area. Graph classification is one of the most important graph data analysis problems, which choose the most probable class labels of graphs using models… read more here.
Keywords: classification; graph data; big graph; graph classification ... See more keywords
Graph data modelling with a Safety II perspective: enhancing disaster response in Japan
Sign Up to like & getrecommendations! Published in 2025 at "Journal of Risk Research"
DOI: 10.1080/13669877.2025.2485034
Abstract: Abstract Disaster record reports serve as critical support for electricity company executives in formulating emergency countermeasures. Recognizing the urgency of accessing and managing disaster response information during crises, this study introduces a graph data modelling… read more here.
Keywords: data modelling; disaster; graph data; disaster response ... See more keywords
Hierarchical Model Selection for Graph Neural Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Access"
DOI: 10.1109/access.2023.3246128
Abstract: Node classification on graph data is a major problem in machine learning, and various graph neural networks (GNNs) have been proposed. Variants of GNNs such as H2GCN and CPF outperform graph convolutional networks (GCNs) by… read more here.
Keywords: hierarchical model; neural networks; model selection; graph neural ... See more keywords
The Property Graph Data Format (PGDF)
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Access"
DOI: 10.1109/access.2024.3485685
Abstract: Property graphs are popular in both industry and academia due to their versatility in modeling complex data across diverse application domains, ranging from social networks to knowledge graphs. Despite their popularity, there is no standardized… read more here.
Keywords: pgdf; property; graph data; graph ... See more keywords
Distributed and Privacy Preserving Graph Data Collection in Internet of Thing Systems
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3112186
Abstract: Internet of Thing (IoT) systems have been treated as a novel platform for graph data acquisition. Contents like dynamic network topology, organization and control flows, and interactions among monitored objects all contribute to the huge… read more here.
Keywords: internet thing; data collection; privacy; collection ... See more keywords
A Diagnostic Framework for Harmonic Drives Based on Dynamic Graph Data Augmentation and Adaptive Knowledge Distillation for Graphs
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2025.3580568
Abstract: The operational state of harmonic drives demonstrates nonlinear and nonstationary characteristics, which pose challenges for traditional methods to extract features. Graph neural networks (GNNs) have shown significant potential in harmonic drive fault diagnosis owing to… read more here.
Keywords: graph data; distillation; harmonic drives; data augmentation ... See more keywords
Maritime Target Detection Based on Radar Graph Data and Graph Convolutional Network
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Geoscience and Remote Sensing Letters"
DOI: 10.1109/lgrs.2021.3133473
Abstract: Due to the complex sea clutter environment and target features, the conventional statistical theory-based methods cannot achieve high performance in maritime target detection tasks. Conventional deep learning, such as convolutional neural networks (CNNs)-based target detection… read more here.
Keywords: maritime target; detection; graph data; target detection ... See more keywords
A Deep Learning-Based Feature Extraction and Knowledge Discovery Method for Spatiotemporal Graph Data
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Computational Social Systems"
DOI: 10.1109/tcss.2024.3501680
Abstract: With the rapid development of new technologies such as the Internet of Things and mobile Internet, human society can obtain a large number of spatiotemporal data such as time sequence sensing data and video data.… read more here.
Keywords: graph data; knowledge discovery; graph; spatiotemporal graph ... See more keywords
De-SAG: On the De-Anonymization of Structure-Attribute Graph Data
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Transactions on Dependable and Secure Computing"
DOI: 10.1109/tdsc.2017.2712150
Abstract: In this paper, we study the impacts of non-Personal Identifiable Information (non-PII) on the privacy of graph data with attribute information (e.g., social networks data with users’ profiles (attributes)), namely Structure-Attribute Graph (SAG) data, both… read more here.
Keywords: anonymization; graph; graph data; structure attribute ... See more keywords
Differentially Private Weighted Graphs Publication Under Continuous Monitoring
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Transactions on Mobile Computing"
DOI: 10.1109/tmc.2024.3514153
Abstract: Graph data analysis has been used in various real-world applications to improve services or scientific research, which, however, may expose sensitive personal information. Differential privacy (DP) has become the gold standard for publishing graph data… read more here.
Keywords: weighted graph; weighted graphs; differentially private; graph data ... See more keywords
GPENs: Graph Data Learning With Graph Propagation-Embedding Networks.
Sign Up to like & getrecommendations! Published in 2021 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2021.3120100
Abstract: Compact representation of graph data is a fundamental problem in pattern recognition and machine learning area. Recently, graph neural networks (GNNs) have been widely studied for graph-structured data representation and learning tasks, such as graph… read more here.
Keywords: representation; propagation; graph propagation; propagation embedding ... See more keywords