Microsoft Certified: Azure AI Engineer AssociateImplement natural language processing solutionsEasy
An insurance company wants to automate the processing of customer claims submitted as free-form text. The goal is to accurately categorize each claim into predefined types, such as 'auto accident', 'property damage', 'medical emergency', or 'life insurance claim', to route them to the correct department. The company has a large historical dataset of categorized claims. Which Azure AI Language feature should be used?
- ASentiment Analysis
- BAbstractive Summarization
- CCustom Text Classification
- DKey Phrase Extraction
Show answer & explanationAnswer & explanation
Correct answer: C. Custom Text Classification
The requirement to 'accurately categorize each claim into predefined types' using a 'large historical dataset of categorized claims' is the core function of Custom Text Classification. This feature allows you to train a model to assign custom labels (categories) to text based on your own data.
Why the other options are wrong
- A. Sentiment Analysis determines emotional tone, not claim type.
- B. Abstractive Summarization generates summaries, not categories.
- D. Key Phrase Extraction identifies important concepts, not categories for routing.
Custom Text Classification
An Azure AI Language feature that allows users to train a custom machine learning model to classify text into their own defined categories or labels, using their specific domain data.
- Trains a model with user-provided text and labels.
- Automates the categorization of unstructured text.
- Useful for routing, content organization, and trend analysis.
Memory trick: Custom Text Classification sorts your specific documents.