1. EXECUTIVE SUMMARY
2. MARKET SNAPSHOT
2.1. Market Overview
2.2. Market Definition
2.3. Scope of the Study
2.4. Market Segmentation
3. BUSINESS LANDSCAPE
3.1. Market Drivers
3.2. Market Restraints
3.3. Market Opportunities
3.4. Porter’s Five Forces Analysis
3.5. Industry Value Chain Analysis
3.6. Policies and Regulations
3.7. Strategic Recommendations
4. TECHNOLOGICAL OUTLOOK
5. GRAPH NEURAL NETWORKS (GNNS) MARKET BY TYPE OF GNN ARCHITECTURE
5.1. Introduction
5.2. Graph Convolutional Networks (GCN)
5.3. Spatial and Spectral-based GNNs
5.4. Graph Recurrent Networks (GRN)
5.5. Graph Attention Networks (GAT)
6. GRAPH NEURAL NETWORKS (GNNS) MARKET BY APPLICATION
6.1. Introduction
6.2. Fraud Detection and Risk Assessment
6.3. Traffic flow prediction & Analysis
6.4. Drug Discovery and Molecular Prediction
6.5. Natural Language Processing
6.6. Computer Vision
6.7. Others
7. GRAPH NEURAL NETWORKS (GNNS) MARKET BY END-USER
7.1. Introduction
7.2. E-Commerce & Retail
7.3. Healthcare
7.4. Finance and Insurance
7.5. Transportation
7.6. Manufacturing
7.7. Others
8. GRAPH NEURAL NETWORKS (GNNS) MARKET BY GEOGRAPHY
8.1. Introduction
8.2. North America
8.2.1. United States
8.2.2. Canada
8.2.3. Mexico
8.3. South America
8.3.1. Brazil
8.3.2. Argentina
8.3.3. Others
8.4. Europe
8.4.1. United Kingdom
8.4.2. Germany
8.4.3. France
8.4.4. Italy
8.4.5. Others
8.5. Middle East & Africa
8.5.1. Saudi Arabia
8.5.2. UAE
8.5.3. Others
8.6. Asia Pacific
8.6.1. Japan
8.6.2. China
8.6.3. India
8.6.4. South Korea
8.6.5. Taiwan
8.6.6. Others
9. COMPETITIVE ENVIRONMENT AND ANALYSIS
9.1. Major Players and Strategy Analysis
9.2. Market Share Analysis
9.3. Mergers, Acquisitions, Agreements, and Collaborations
9.4. Competitive Dashboard
10. COMPANY PROFILES
10.1. Amazon
10.2. Alibaba
10.3. DeepMind (Alphabet Inc)
10.4. NVIDIA Corporation
10.5. Syntiant
10.6. IBM
11. APPENDIX
11.1. Currency
11.2. Assumptions
11.3. Base and Forecast Years Timeline
11.4. Key benefits for the stakeholders
11.5. Research Methodology
11.6. Abbreviations