AI-102 Plan and manage an Azure AI solution Practice Question
Your organization is using Azure AI Search with semantic ranking. Users report that search results are not showing relevant documents at the top. You need to improve relevance. What should you configure?
⚠ Common exam trap
Microsoft often tests the misconception that enabling semantic ranking is automatic with the service tier, but candidates must explicitly configure a semantic configuration on the index and specify it in the query request to activate the feature.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable semantic search configuration on the index
Semantic search configuration is required to enable semantic ranking, which uses deep learning models to re-rank search results based on contextual relevance rather than just keyword matching. Without this configuration, the index cannot leverage semantic ranking even if the service tier supports it, so enabling it directly addresses the user's complaint about irrelevant documents appearing at the top.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Add synonyms to the index
Why it's wrong here
Synonyms expand queries but don't improve ranking.
- ✗
Define a custom scoring profile
Why it's wrong here
Custom scoring profiles are for simple field boosting, not semantic understanding.
- ✓
Enable semantic search configuration on the index
Why this is correct
Semantic search configuration enables L2 ranking models for better relevance.
- ✗
Change the index analyzer to a different language analyzer
Why it's wrong here
Analyzers affect tokenization, not relevance ranking.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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