Eleven Papers Map the Frontier of Data Spaces and Data Governance
A new special issue of Data Science and Engineering collects eleven peer-reviewed papers on data spaces, data governance, and data-driven ...
Tag: Graph Neural Networks
Dynamic Graph AI Model Hits Nearly 96% Accuracy in Traffic Congestion Prediction
A new dynamic graph neural framework called GAMMA-Traffic updates road-network connections in real time using cross-correlation analysis, reporting up to ...
Graph neural network method boosts detection of rare cyberattacks in imbalanced data
A new graph neural network framework called EGNN expands rare attack samples and uses threshold-controlled pseudo-labeling to improve intrusion detection ...
Edge Weight Beats Node Degree When NAT Hides Attackers in Network Graphs
A study of the CICIDS2017 DDoS capture shows node-degree graph features fail under NAT identity collapse while edge-weight concentration separates ...
COMPASS model learns per-user spectral allocation for robust recommendations
A new recommender model called COMPASS learns a user-specific allocation over spectral bands instead of a fixed truncation rank, improving ...
Normalization Stabilizes Shallow Graph Networks but Cannot Stop Deep Oversmoothing
A controlled study of 3,600 runs finds normalization schemes help mainly at shallow depths while graph homophily predicts how accuracy ...
Greedy Deep Kernel Method Outperforms Neural Networks in Approximation Tests
Researchers combined greedy kernel interpolation with trainable deep kernels and found the resulting models matched or beat neural networks in ...
Grouping Students by Behavior Helps AI Diagnose What They Know
A new graph-based framework groups similar learners and augments sparse data to improve cognitive diagnosis predictions across three public datasets.
Spark-based graph motifs expose fraud rings in massive transaction networks
Researchers have built a Spark GraphFrames framework that enumerates millions of transaction cycles and filters them with timestamp and amount ...
New AI Model Scales Up Learning for Knowledge Graphs Full of Unseen Entities
A new contrastive learning framework called VMCL improves knowledge graph embedding for unseen entities and shows smooth, predictable gains as ...
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Mothers who receive childcare support from maternal grandparents show more parental warmth, finds NTU Singapore study
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University of Seville Breaks 120-Year-Old Mystery, Revises a Key Einstein Concept
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Bee body mass, pathogens and local climate influence heat tolerance
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Researchers record first-ever images and data of a shark experiencing a boat strike
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Groundbreaking Clinical Trial Reveals Lubiprostone Enhances Kidney Function
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