AI-102 Question 179
Single answerYou are designing an Azure solution to analyze customer feedback stored in text files using the Text Analytics API. The goal is to extract the most important keywords or phrases from the feedback for further analysis. Which step should you take to achieve this using the Azure AI service?
- A
Use the Key Phrases Extraction feature of the Azure Text Analytics API
- B
Use the Sentiment Analysis feature of the Azure Text Analytics API
- C
Train a custom model in Azure Machine Learning to extract keywords
- D
Use the Named Entity Recognition (NER) feature of the Azure Text Analytics API
Show answer and explanation
Correct answer: A
Explanation
The Key Phrases Extraction feature of Azure Text Analytics API is the most efficient and straightforward way to extract important keywords or phrases from text data. It is a pre-built functionality that does not require any additional training or customization, making it ideal for this scenario.
- A. Correct.
This is the correct choice because the Key Phrases Extraction feature is specifically designed to identify the most important keywords or phrases in a given text.
- B. Incorrect.
This is incorrect because Sentiment Analysis is used to determine the sentiment (positive, negative, or neutral) of text, not to extract key phrases.
- C. Incorrect.
This is incorrect because training a custom model is unnecessary when Azure Text Analytics provides a pre-built Key Phrases Extraction feature.
- D. Incorrect.
This is incorrect because Named Entity Recognition identifies specific entities like names, locations, or dates, not key phrases.