Implement knowledge mining and information extraction solutions →easyMultiple ChoiceObjective-mapped
AI-102 Practice Question: Implement knowledge mining and information extraction solutions
A company uses Azure AI Search to index customer support transcripts. They want to enable users to find relevant answers by asking natural language questions. Which feature should they enable in the search service?
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 improves relevance by understanding natural language queries and providing answer-style results. Synonym maps (B) help with query expansion but not natural language understanding. Cognitive skills (C) are used for enrichment during indexing, not query-time interpretation. Knowledge mining (D) is a broader process that encompasses multiple services, not a specific feature of Azure AI Search.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Semantic search
Why this is correct
Semantic search improves relevance by understanding natural language queries and providing answer-style results.
- ✗
Synonym maps
Why it's wrong here
Synonym maps help with query expansion but do not provide natural language understanding.
- ✗
Cognitive skills
Why it's wrong here
Cognitive skills are used for enrichment during indexing, not for query-time natural language interpretation.
- ✗
Knowledge mining
Why it's wrong here
Knowledge mining is a broader concept that encompasses multiple services, not a specific feature within Azure AI Search.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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