Correct Answers: A and D
RentMe mobile application should use Text recognition and Entity extraction models.
A Text recognition model extracts text from the images with printed or handwritten text. Using this model, you can extract information from the pictures of the driver’s license, credit card and car’s plates.
An Entity extraction model analyzes a text, determines the text language, and extracts specific entities defined in a model. The standard model includes 28 such entities, like email address, date-time, phone number, etc. You can add other entities by training your model. You can use this model with Text recognition output to extract the data points (entities) from driver’s license, credit card, and car’s plates. Then you can present to a user the extracted information for the review and create a new account. Option B is incorrect because the Key Phrase Extraction model analyzes the text and extracts the most important phrases. This model creates text summaries. But it does not read a text in images and extract the data points from the text.
Option C is incorrect because the Sentiment Analysis model analyzes a text on positive, negative, or neutral sentiment. But this model does not read a text in images and extract the data points from the text.
Option E is incorrect because the Category classification model analyzes a text, determines the text language, and classifies text according to the predefined or trained categories. But this model does not read a text in images and extract the data points from the text.
For more information about AI Builder models, please visit the below URLs:
https://docs.microsoft.com/en-us/ai-builder/use-in-flow-overview
https://docs.microsoft.com/en-us/ai-builder/prebuilt-text-recognizer-component-in-powerapps
https://docs.microsoft.com/en-us/ai-builder/prebuilt-entity-extraction