Semantic Relevance Scoring
Definition
Semantic Relevance Scoring measures how closely content matches the contextual meaning of a query rather than its exact keywords.
Why It Matters
AI systems rely heavily on semantic similarity rather than keyword frequency.
How It Works
Embedding models compare vector similarity between query and content.
Use Cases
- Optimizing hybrid search
- Improving vector retrieval
- Enhancing answer accuracy
Best Practices
- Use intent-driven headings
- Maintain topic clarity
- Avoid keyword stuffing
- Strengthen contextual depth
Frequently Asked Questions
What is semantic relevance? +
It measures contextual meaning alignment between query and content.
Does keyword density matter? +
Less than semantic clarity in AI systems.
How is it calculated? +
Using embedding similarity scores.
Related Terms
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