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A logistics company is building an automated system to process incoming customer emails. The system needs to automatically categorize emails into predefined categories such as 'Order Tracking', 'Billing Inquiry', or 'Complaint' to route them to the correct department. The company has a large dataset of previously categorized emails. Which Azure AI Language feature is best suited for this custom classification task?
- APre-built Text Summarization
- BCustom Text Classification
- CNamed Entity Recognition (NER)
- DLanguage Detection
Show answer & explanationAnswer & explanation
Correct answer: B. Custom Text Classification
Custom Text Classification allows you to train a model using your own labeled data to categorize text into custom-defined categories. This is exactly what's needed for routing emails based on specific business categories like 'Order Tracking' or 'Billing Inquiry'.
Why the other options are wrong
- A. Text Summarization condenses text, it does not categorize it.
- C. NER extracts specific entities (like dates or names), it does not categorize the entire document.
- D. Language Detection identifies the language of the text, not its category.
Custom Text Classification
An Azure AI Language feature that enables users to train custom machine learning models to classify text into predefined, domain-specific categories using their own labeled datasets. It's ideal for tasks like email routing, content tagging, or sentiment categorization.
- Classifies text into user-defined categories.
- Requires custom labeled training data.
- Useful for domain-specific text routing and tagging.
Memory trick: Custom Classifies, routing emails right.