AI-900: How to Use Form Recognizer Service for Extracting Data from Forms

Learn how to use Form Recognizer service for extracting data from forms, such as invoices, receipts, and catalogs. Find out which two scenarios are suitable for using Form Recognizer service and how it can help you automate data extraction and analysis.

Question

In which two scenarios can you use the Form Recognizer service? Each correct answer
presents a complete solution.

NOTE: Each correct selection is worth one point.

A. Extract the invoice number from an invoice.
B. Translate a form from French to English.
C. Find image of product in a catalog.
D. Identity the retailer from a receipt.

Answer

A. Extract the invoice number from an invoice.
D. Identity the retailer from a receipt.

Explanation

The correct answer is A and D. You can use the Form Recognizer service to extract the invoice number from an invoice and to identify the retailer from a receipt.

The Form Recognizer service is a cloud-based Azure AI service that uses machine learning to analyze text and structured data from your documents. It enables you to effectively manage the velocity at which data is collected and processed and is key to improved operations, informed data-driven decisions, and enlightened innovation.

The Form Recognizer service offers three types of document analysis models: Read, Layout, and General document. These models enable text extraction from forms and documents and return structured business-ready content ready for your organization’s action, use, or progress.

The Form Recognizer service also offers prebuilt models and custom models. Prebuilt models enable you to add intelligent document processing to your apps and flows without having to train and build your own models. Custom models are trained using your labeled datasets to extract distinct data from forms and documents, specific to your use cases.

In scenario A, you can use the prebuilt Invoice model to extract the invoice number from an invoice. The Invoice model extracts customer and vendor details, invoice ID, total tax, subtotal, line items, and more from invoices. You can also use a custom extraction model to extract a specific schema from your invoices.

In scenario D, you can use the prebuilt Receipt model to identify the retailer from a receipt. The Receipt model extracts time and date of the transaction, merchant information, amounts of taxes, totals, and more from receipts. You can also use a custom extraction model to extract a specific schema from your receipts.

In scenario B, you cannot use the Form Recognizer service to translate a form from French to English. The Form Recognizer service does not provide translation capabilities. You can use the Translator service to translate text from one language to another.

In scenario C, you cannot use the Form Recognizer service to find an image of a product in a catalog. The Form Recognizer service does not provide image search capabilities. You can use the Bing Image Search service to find images of products from the web.

Reference

Microsoft Azure Products > Cognitive Services > Azure Cognitive Services

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