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Knowledge Graph
Definition
Knowledge Graph
A knowledge graph is a structured database representing real-world entities and their relationships.
TL;DR
Key Definition
Knowledge graphs organize information into nodes (entities) and edges (relationships). Google, Bing, and LLMs use these graphs to understand "Hikoo is a GEO tool" rather than just "Hikoo" and "GEO" as words.
Importance
Why It Matters
- Foundation of AI semantic understanding
- Enables brand-concept associations
- Improves response accuracy about you
- Source of Google Knowledge Panels
How It Works
Knowledge graphs structure information in triplets: subject-predicate-object.
Triplet Structure
"Hikoo" (subject) - "is a" (predicate) - "GEO tool" (object). These triplets form a knowledge network.
Data Sources
Schema.org, Wikipedia, structured databases, automatic text extraction.
Metrics
How to Measure It
- Presence in Google Knowledge Graph (via API)
- Number of established relationships
- Attribute accuracy
Pitfalls
Common Mistakes
- Ignoring schema.org for structured data
- Contradictory information between sources
- Lack of relational context
Quick Checklist
Follow these steps to get started.
- Implement complete schema.org on your site
- Ensure information consistency everywhere
- Create content establishing your relationships (partners, industry)
- Check your presence in Google Knowledge Graph
Examples
Entity Relationship
The graph knows that "Hikoo" → "offers" → "GEO analysis", and that "GEO" → "is related to" → "SEO", creating semantic connections.