A.To define the document types and the pieces of information targeted for data extraction (fields) for each document type.

B.To organize knowledge by using a controlled vocabulary to make it easier to find related information.

C.To apply relationship schemas other than parent-child hierarchies, such as network structures on the processed data.

D.To apply rigor in the taxonomy of data, ensuring any newly discovered object fits into one and only one category or object.

A.Simply run the existing tests

B.Based on the use case developed, create test data to test existing and new tests.

C.Use them as a template to create other tests.

D.Based on the use case developed, create test data to test existing tests.

A.Document Manager.

B.Digitization.

C.ML Extractor.

D.Data Manager.

A.IntelligentOCR is a UiPath Studio activity package that contains all the activities needed to enable information extraction, while OCR (Optical Character Recognition) is a method that reads text from images, recognizing each character and its position.

B.OCR (Optical Character Recognition) is a method that reads text from images, recognizing each character and its position, while IntelligentOCR is an enhanced version of it that can also work with noisier input data.

C.OCR (Optical Character Recognition) is a UiPath Studio activity package that contains IntelligentOCR as an activity used to read text from images, recognizing each character and its position. OCR is widely used in Document Understanding processes.

D.IntelligentOCR is simply a rebranding of the OCR (Optical Character Recognition), both of them being methods that read text from images, recognizing each character and its position.

A.Hybrid data extraction.

B.Model-based data extraction.

C.Rule-based data extraction.

D.Manual data extraction.