In which scenario should you use key phrase extraction?
A.
translating a set of documents from English to German
B.
generating captions for a video based on the audio track
C.
identifying whether reviews of a restaurant are positive or negative
D.
identifying which documents provide information about the same topics
The Answer Is:
D
This question includes an explanation.
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) official study guide and Microsoft Learn module “Extract insights from text with the Text Analytics service”, key phrase extraction is a feature of the Text Analytics service that identifies the most important words or phrases in a given document. It helps summarize the main ideas by isolating significant concepts or terms that describe what the text is about.
In this scenario, the goal is to determine which documents share similar topics or themes. By extracting key phrases from each document (for example, “policy renewal,” “coverage limits,” “claim process”), you can compare and categorize documents based on overlapping keywords. This is exactly how key phrase extraction is used—to summarize and group text content by topic relevance.
The other options do not fit this use case:
A. Translation uses the Translator service, not key phrase extraction.
B. Generating video captions involves speech recognition and computer vision.
C. Identifying sentiment relates to sentiment analysis, not key phrase extraction.
[Reference:Microsoft Learn – Extract insights from text with Text Analytics, , , , ]
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