- A
Synonym maps
Why wrong: Synonym maps expand queries but do not directly improve ranking.
- B
Semantic search
Semantic search uses AI to understand the intent of the query and improve ranking.
- C
Suggesters
Why wrong: Suggesters provide autocomplete suggestions, not relevance.
- D
Scoring profiles
Scoring profiles allow you to boost results based on field values or freshness.
- E
Filterable fields
Why wrong: Filterable fields narrow results but do not affect ranking.
Question 170 of 993
Implement knowledge mining and information extraction solutions →easyMultiple SelectObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
This AI-102 practice question tests your understanding of implement knowledge mining and information extraction solutions. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which TWO features of Azure AI Search allow you to improve the relevance of search results for users?
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
✓
Semantic search
Semantic search (B) improves relevance by using deep neural networks to understand the intent and context behind a query, re-ranking results based on semantic relevance rather than just keyword matching. This allows users to find more meaningful results even when their query doesn't exactly match indexed terms.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Synonym maps
Why it's wrong here
Synonym maps expand queries but do not directly improve ranking.
- ✓
Semantic search
Why this is correct
Semantic search uses AI to understand the intent of the query and improve ranking.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Suggesters
Why it's wrong here
Suggesters provide autocomplete suggestions, not relevance.
- ✓
Scoring profiles
Why this is correct
Scoring profiles allow you to boost results based on field values or freshness.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Filterable fields
Why it's wrong here
Filterable fields narrow results but do not affect ranking.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse features that expand recall (synonym maps) or improve user experience (suggesters) with features that directly improve relevance ranking, leading them to select A or C instead of the correct scoring profiles and semantic search.
Detailed technical explanation
How to think about this question
Semantic search in Azure AI Search uses a transformer-based re-ranker (like Microsoft's Turing model) that scores each document-query pair on a scale of 0–4, then re-orders top results from the initial BM25 retrieval. This re-ranking can significantly boost precision for natural language queries, such as 'best budget hotels in Seattle' versus a simple keyword match. Scoring profiles, on the other hand, allow you to boost results based on field weights, freshness, or custom functions—offering fine-grained control over relevance without semantic understanding.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A healthcare organisation deploys an application with a public-facing web tier and a private database tier. The database subnet has no public IP and only accepts connections from the web tier's security group. Questions like this test whether you can design cloud network isolation using VNets/VPCs, subnets, and security group rules.
What to study next
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FAQ
Questions learners often ask
What does this AI-102 question test?
Implement knowledge mining and information extraction solutions — This question tests Implement knowledge mining and information extraction solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Semantic search — Semantic search (B) improves relevance by using deep neural networks to understand the intent and context behind a query, re-ranking results based on semantic relevance rather than just keyword matching. This allows users to find more meaningful results even when their query doesn't exactly match indexed terms.
What should I do if I get this AI-102 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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Last reviewed: Jul 4, 2026
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