Microsoft Azure AI Fundamentals (AI-900)Describe features of Natural Language Processing (NLP) workloads on AzureMedium
A marketing team wants to analyze customer feedback from various online sources to understand if the overall sentiment towards their new product launch is positive, negative, or neutral. They also need to identify the main topics or features customers are discussing. Which two Azure Cognitive Service for Language features should they utilize?
- ALanguage Detection and Text Generation
- BNamed Entity Recognition and Entity Linking
- CCustom Text Classification and Custom NER
- DSentiment Analysis and Key Phrase Extraction
Show answer & explanationAnswer & explanation
Correct answer: D. Sentiment Analysis and Key Phrase Extraction
Sentiment Analysis will determine the emotional tone (positive, negative, neutral) of the customer feedback. Key Phrase Extraction will identify the main topics or features being discussed within that feedback, directly addressing both parts of the requirement.
Why the other options are wrong
- A. Language Detection identifies language; Text Generation creates new text, neither directly addresses sentiment or topics.
- B. NER identifies entities; Entity Linking resolves them, not for sentiment or general topic identification.
- C. Custom Text Classification categorizes documents; Custom NER extracts specific custom entities, not general sentiment or key phrases.
Sentiment & Key Phrase Analysis
A combination of NLP tasks to understand the emotional tone of text and extract its core topics or concepts.
- Commonly used in customer feedback analysis.
- Sentiment provides emotional context.
- Key phrases reveal discussed subjects.
Memory trick: Feel the sentiment, find the key phrases.