Microsoft Azure AI Fundamentals (AI-900)Describe features of Natural Language Processing (NLP) workloads on AzureEasy
A content platform receives thousands of user-submitted articles daily. To quickly determine if an article's content aligns with its stated category (e.g., a 'Sports' article truly discusses sports), the platform needs to automatically assign predefined categories to each new article. Which NLP capability is best suited for this automated categorization?
- ANamed Entity Recognition (NER)
- BAnomaly Detection
- CText Summarization
- DText Classification
Show answer & explanationAnswer & explanation
Correct answer: D. Text Classification
Text Classification is precisely the NLP capability used to assign predefined categories or labels to text documents. This is ideal for automatically verifying if an article's content matches its stated category.
Why the other options are wrong
- A. NER identifies specific entities, not overall document categories.
- B. Anomaly Detection identifies unusual patterns, not standard categorization.
- C. Text Summarization condenses text, not categorizes it.
Text Classification
The NLP task of assigning one or more predefined categories or labels to a piece of text.
- Used for spam detection, content routing, sentiment analysis (as a binary classification).
- Requires a set of predefined categories.
- Can be custom-trained for specific domains.
Memory trick: Classify text to put it in the right folder.