Applied Graph Data Science

1. Introduction to Graph neural network: A systematic review of trends, methods, and applications
2. Chronological Reasoning in Knowledge Graphs using AI and ML: A novel framework
3. Graph-based Approach on Financial Fraudulent Detection and Prediction
4. The Power of Graph Neural Networks: From Theory to Application
5. Delineating Graph Neural Networks (GNNs) and the Real-World Applications
6. Graph Techniques for Enhancing Knowledge Graph Integration: A Comprehensive Study and Applications
7. Graphs, Language Models, and NLP: The Future of Search Engines
8. Graph Data Science and ML techniques: Applications and future
9. Innovative Feature Engineering Methods for Graph Data Science
10. Graph Neural Networks: Insight and Applications
11. Graph-Theoretic Analysis for Eco-Efficient Textile Weaving Patterns
12. Quantum-assisted Graph Networks: Algorithmic Innovations and Optimization Strategies for Large-Scale Social Communities
13. Using physics-informed AI and graph-based quantum computing for natural catastrophic analysis: Future perspectives
14. Integrating Machine Learning and Deep Learning Algorithms in Knowledge Graph for Disease Screening and Cataloging: Tools and Approaches for Drug Invention and Additive Manufacturing
15. Analysing Social network with dynamic graphs: unravelling the ever-evolving connection
16. Transforming E-commerce with Graph Neural Networks: Enhancing Personalization, Security, and Business Growth
17. On Rings Domination in Soft Graphs
18. Graph Data Science: Applications and Future
19. Verification of MPI programs via compilation into Petri nets
20. Demonstration and Analysis of the Performance of Image Caption Generator: An Effort for Visually Impaired Candidates for Smart Cities 5.0