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NEW QUESTION # 185
Which technology enables UiPath Communications Mining to analyze and enable action on messages?
Answer: D
Explanation:
UiPath Communications Mining is a new capability to understand and automate business communications. It uses state-of-the-art AI models to turn business messages-from emails to tickets-into actionable data. It does this in real time and on all major business communications channels1. Natural Language Processing (NLP) is the branch of AI that deals with analyzing, understanding, and generating natural language. NLP enables UiPath Communications Mining to extract the most important data from any message, such as reasons for contact, data fields, and sentiment2. NLP also allows UiPath Communications Mining to deploy custom AI models in hours, not weeks, by using automatic labeling and annotation2.
References: 2 Communications Mining - Automate Business Communications | UiPath 1 Introducing UiPath Communications Mining | UiPath
NEW QUESTION # 186
When is it recommended to use Main-ActionCenter in the context of the Document Understanding Process?
Answer: C
NEW QUESTION # 187
Which of the following extractors can be used for Data Extraction Scope activity?
Answer: B
Explanation:
The Data Extraction Scope activity provides a scope for extractor activities, enabling you to configure them according to the document types defined in your taxonomy. The output of the activity is stored in an ExtractionResult variable, containing all automatically extracted data, and can be used as input for the Export Extraction Results activity. This activity also features a Configure Extractors wizard, which lets you specify exactly what fields from the document types defined in the taxonomy you want to extract1.
The extractors that can be used for Data Extraction Scope activity are:
* Regex Based Extractor: This extractor enables you to use regular expressions to extract data from text documents. You can define your own expressions or use the predefined ones from the Regex Based Extractor Configuration wizard2.
* Form Extractor: This extractor enables you to extract data from semi-structured documents, such as invoices, receipts, or purchase orders, based on the position and relative distance of the fields. You can define the templates for each document type using the Form Extractor Configuration wizard3.
* Intelligent Form Extractor: This extractor enables you to extract data from semi-structured documents, such as invoices, receipts, or purchase orders, based on the labels and values of the fields. You can define the fields for each document type using the Intelligent Form Extractor Configuration wizard.
* Machine Learning Extractor: This extractor enables you to extract data from any type of document, using a machine learning model that is trained on your data. You can use the predefined models from UiPath or your own custom models hosted on AI Center or other platforms. You can configure the fields and the model for each document type using the Machine Learning Extractor Configuration wizard.
References: 1: Data Extraction Scope 2: Regex Based Extractor 3: Form Extractor 4: Intelligent Form Extractor
5: Machine Learning Extractor
NEW QUESTION # 188
Which of the following is an indicator that sufficient training has been completed for a model in UiPath Communications Mining?
Answer: B
NEW QUESTION # 189
What is the purpose of the End Process in the Document Understanding Process?
Answer: B
Explanation:
The End Process is the final stage of the Document Understanding Process, which is a fully functional UiPath Studio project template based on a document processing flowchart. The End Process is responsible for setting the queue transaction status, logging the results, and performing any post processing or cleaning actions if needed. The End Process sets the queue transaction status as Successful if the document was processed without any exception, and as Failed if an exception occurred, either a Business Exception (such as invalid data) or a System Exception (such as network failure). The End Process also adds the extracted data and the validation status as output arguments to the queue transaction. The End Process also logs the processing statistics, such as the number of documents processed, the number of exceptions, the average processing time, and the accuracy rate. The End Process also performs any post processing or cleaning actions, such as deleting temporary files, closing applications, or sending notifications1.
References: 1: Document Understanding Process: Studio Template
NEW QUESTION # 190
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