Knowledge Graphs: Semantic Reasoning Meets Graph Architecture
On this page
- Introduction
- Core Components of a Knowledge Graph
- 1. Entities (Nodes)
- 2. Relationships (Edges)
- 3. Ontology / Schema Layer
- 4. Named Graphs / Contexts
- Knowledge Graph vs. Labeled Property Graph
- Advanced Data Modeling in KGs
- Reasoning Capabilities
- Querying Knowledge Graphs (SPARQL)
- Practical Use Cases
- 1. Enterprise Knowledge Management
- 2. AI/ML Feature Enrichment
- 3. Biomedical Discovery
- 4. Financial Compliance
- Mermaid Diagram
- Schema Constraints with SHACL
- Performance Optimization Strategies
- 1. Materialized Inferences
- 2. Named Graph Partitioning
- 3. Hybrid Indexing
- Migration Strategies
- From Relational Databases
- From Property Graphs
- Advanced SPARQL Queries
- 1. Semantic Entity Resolution
- 2. Transitive Location Reasoning
- 3. Concept Hierarchy Query
- Industry Adoption
- Limitations and Challenges
- Future Trends
- 1. Neuro-Symbolic Systems
- 2. Federated Knowledge Graphs
- 3. Graph Embeddings & GNNs
- 4. KG Construction from LLMs
- Conclusion
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