mlsanityData to 14 Oct 2026

Graph Neural Network-Based Entity Extraction and Relationship Reasoning in Complex Knowledge Graphs

arXiv 2411.15195 ↗First posted 19 Nov 2024cs.CL cs.AI cs.LGcited by 9

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Abstract (arXiv)

This study proposed a knowledge graph entity extraction and relationship reasoning algorithm based on a graph neural network, using a graph convolutional network and graph attention network to model the complex structure in the knowledge graph. By building an end-to-end joint model, this paper achieves efficient recognition and reasoning of entities and relationships. In the experiment, this paper compared the model with a variety of deep learning algorithms and verified its superiority through indicators such as AUC, recall rate, precision rate, and F1 value. The experimental results show that the model proposed in this paper performs well in all indicators, especially in complex knowledge graphs, it has stronger generalization ability and stability. This provides strong support for further research on knowledge graphs and also demonstrates the application potential of graph neural networks in entity extraction and relationship reasoning.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 12 of its 19 references that are in the map. First posted on arXiv 19 Nov 2024.

Builds on

12 of 19 references.

References · 12

  1. 2024Transforming Multidimensional Time Series into Interpretable Event Sequences for Advanced Data Miningcited by 47
  2. 2024Self-Supervised Graph Neural Networks for Enhanced Feature Extraction in Heterogeneous Information Networkscited by 33
  3. 2024Advanced RAG Models with Graph Structures: Optimizing Complex Knowledge Reasoning and Text Generationcited by 13
  4. 2024Emotion-Aware Interaction Design in Intelligent User Interface Using Multi-Modal Deep Learningcited by 13
  5. 2024Metric Learning for Tag Recommendation: Tackling Data Sparsity and Cold Start Issuescited by 12
  6. 2024A Lightweight GAN-Based Image Fusion Algorithm for Visible and Infrared Imagescited by 11
  7. 2024Efficient and Aesthetic UI Design with a Deep Learning-Based Interface Generation Tree Algorithmcited by 11
  8. 2024Contrastive Learning for Knowledge-Based Question Generation in Large Language Modelscited by 8
  9. 2024A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Miningcited by 8
  10. 2024Optimizing News Text Classification with Bi-LSTM and Attention Mechanism for Efficient Data Processingcited by 7
  11. 2024Automated Genre-Aware Article Scoring and Feedback Using Large Language Modelscited by 7
  12. 2024Reinforcement Learning for Adaptive Resource Scheduling in Complex System Environmentscited by 7

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Cited by year

Citing papers per year: 2024: 9.

9 papers.

  1. 2024Adaptive Optimization for Enhanced Efficiency in Large-Scale Language Model Trainingcited by 13
  2. 2024Machine Learning Techniques for Pattern Recognition in High-Dimensional Data Miningcited by 8
  3. 2024AI-Driven Health Monitoring of Distributed Computing Architecture: Insights from XGBoost and SHAPcited by 7
  4. 2024Advanced Risk Prediction and Stability Assessment of Banks Using Time Series Transformer Modelscited by 6
  5. 2024Dynamic Scheduling Strategies for Resource Optimization in Computing Environmentscited by 6
  6. 2024Optimizing Multi-Task Learning for Enhanced Performance in Large Language Modelscited by 5
  7. 2024Collaborative Optimization in Financial Data Mining Through Deep Learning and ResNeXtcited by 5
  8. 2024Deep Learning in Image Classification: Evaluating VGG19's Performance on Complex Visual Datacited by 3
  9. 2024Dynamic User Interface Generation for Enhanced Human-Computer Interaction Using Variational Autoencoderscited by 2