UIPATH UIPATH-SAIAV1 NEW PRACTICE QUESTIONS - TRUSTWORTHY UIPATH-SAIAV1 EXAM CONTENT

UiPath UiPath-SAIAv1 New Practice Questions - Trustworthy UiPath-SAIAv1 Exam Content

UiPath UiPath-SAIAv1 New Practice Questions - Trustworthy UiPath-SAIAv1 Exam Content

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UiPath Specialized AI Associate Exam (2023.10) Sample Questions (Q122-Q127):

NEW QUESTION # 122
For what type of documents is it recommended to use the RegEx Based Extractor?

  • A. For structured or semi-structured documents where for certain fields, data is always found in a strict, predictable format and context.
  • B. For structured or semi-structured documents in which layouts of different document providers have little to no variation.
  • C. For structured or semi-structured documents in which layouts of different document providers vary greatly.
  • D. For structured or semi-structured documents where the extraction method is based on a set of FlexiCapture definition files.

Answer: A

Explanation:
The RegEx Based Extractor is most effective for documents where data fields follow a strict and predictable format, such as dates, invoice numbers, or specific patterns like email addresses. This method is well-suited for extracting information from structured or semi-structured documents with consistent formats across different documents, making it highly reliable for use cases where patterns are easily identifiable and do not vary significantly.
(Source: UiPath Document Understanding documentation)


NEW QUESTION # 123
How many types of synchronization mechanisms exist in the Document Understanding Process to prevent multiple robots to write in a file at the same time?2

  • A. 0
  • B. 1
  • C. 2
  • D. 3

Answer: A

Explanation:
The Document Understanding Process uses two types of synchronization mechanisms to prevent multiple robots from writing in a file at the same time: file locks and queues. File locks are used to ensure that only one robot can access a file at a time, while queues are used to store the information extracted from the documents and to avoid data loss or duplication. The process uses the following activities to implement these mechanisms:
File Lock Scope: This activity creates a lock on a file or folder and executes a set of activities within it. The lock is released when the scope ends or when an exception occurs. This activity ensures that only one robot can read or write a file or folder at a time, and prevents other robots from accessing it until the lock is released.
Add Queue Item: This activity adds an item to a queue in Orchestrator, along with some relevant information, such as a reference, a priority, or a deadline. The item can be a JSON object, a string, or any serializable .NET type. This activity ensures that the information extracted from the documents is stored in a queue and can be retrieved by another robot or process later.
Get Queue Items: This activity retrieves a collection of items from a queue in Orchestrator, based on some filters, such as status, reference, or creation time. The items can be processed by the robot or passed to another activity, such as Update Queue Item or Delete Queue Item. This activity ensures that the information stored in the queue can be accessed and manipulated by the robot or process.
References: Document Understanding Process: Studio Template, File Lock Scope, Add Queue Item, [Get Queue Items]


NEW QUESTION # 124
What is the name of the web application that allows users to prepare, review, and make corrections to datasets required for Machine Learning models?

  • A. ML Extractor.
  • B. Digitization.
  • C. Document Manager.
  • D. Data Manager.

Answer: D

Explanation:
Data Manager is a web application that allows users to prepare, review, and make corrections to datasets required for Machine Learning models. Data Manager enables users to create and manage datasets, label data, validate and export data, and monitor data quality and progress. Data Manager supports various types of data, such as documents, images, text, and tables. Data Manager is integrated with AI Center, where users can train and deploy Machine Learning models using the datasets created or modified in Data Manager12.
References: 1: Data Manager Overview 2: AI Center - About Datasets


NEW QUESTION # 125
What is the correct order to Configure Extractor Wizard?
Instructions: Drag the Description found on the left and drop on the correct Step found on the right.

Answer:

Explanation:

Explanation:
Here is the correct order to configure the Extractor Wizard in UiPath Document Understanding:
Step 1: Add a Data Extraction Scope activity to the workflow.Step 2: Place one or more extractors.Step 3:
Click on the Configure Extractors button.Step 4: Select the checkboxes next to each field for the extractor type that should be activated.Step 5: Get capabilities (if needed).Step 6: Click on the Save button.
This sequence ensures that the Extractor Wizard is correctly configured to work with the Document Understanding workflow.


NEW QUESTION # 126
What is the Document Object Model (DOM) in the context of Document Understanding?

  • A. The DOM is a JSON object containing information such as name, content type, text length, number of pages, page rotation, detected language, content, and coordinates for the words identified in the file.
  • B. The DOM is a feature that allows you to convert physical documents into virtual objects that can be manipulated using programming code.
  • C. The DOM is a graphical user interface (GUI) tool in UiPath Document Understanding that provides visual representations of documents, making it easier for users to navigate and interact with the content.
  • D. The DOM is a built-in artificial intelligence system that automatically understands and interprets the content and the type of documents, eliminating the need for manual data extraction.

Answer: A

Explanation:
The Document Object Model (DOM) is a data representation of the objects that comprise the structure and content of a document on the web1. In the context of Document Understanding, the DOM is a JSON object that is generated by the Digitize Document activity, which uses the UiPath Document OCR engine to extract the text and layout information from the input document2. The DOM contains the following properties for each document3:
name: The name of the document file.
contentType: The MIME type of the document file, such as application/pdf or image/jpeg.
textLength: The number of characters in the document text.
pages: An array of objects, each representing a page in the document. Each page object has the following properties:
pageNumber: The number of the page, starting from 1.
rotation: The angle of rotation of the page, in degrees. A positive value indicates clockwise rotation, and a negative value indicates counterclockwise rotation.
language: The language code of the page, such as en or fr.
content: An array of objects, each representing a word or a line in the page. Each content object has the following properties:
type: The type of the content, either word or line.
text: The text of the content.
boundingBox: An array of four numbers, representing the coordinates of the top-left and bottom-right corners of the content, in the format [x1, y1, x2, y2]. The coordinates are relative to the page, with the origin at the top-left corner, and the unit is pixel.
confidence: A number between 0 and 1, indicating the confidence level of the OCR engine in recognizing the content.
The DOM can be used as an input for other activities in the Document Understanding framework, such as Classify Document Scope, Data Extraction Scope, or Export Extraction Results. The DOM can also be manipulated using programming code, such as JavaScript or Python, to perform custom operations on the document data.
References:
1: Introduction to the DOM - Web APIs | MDN 2: Digitize Document 3: Document Object Model


NEW QUESTION # 127
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