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UiPath Certified Professional Specialized AI Professional v1.0 Sample Questions (Q169-Q174):

NEW QUESTION # 169
What is the definition of a UiPath Communications Mining data source?

A. A permissioned storage area within the platform which contains communications and labels.
B. A user-permissioned project containing a taxonomy with labels and entities.
C. The model that we create when training the platform to understand the data in those sources.
D. A collection of raw unlabeled communications data of a similar type, that can be associated with up to 10 datasets.

Answer: D

NEW QUESTION # 170
What is Document Understanding?

A. A solution for the processing of Excel files for extracting data tables.
B. A solution that offers the ability to digitize, extract, validate, and train data from documents.
C. A solution for combining different approaches to extract information from workflows.
D. A solution for combining different approaches to extract entities from Word documents such as contracts and agreements.

Answer: B

NEW QUESTION # 171
What can be done in the Reports section of the dataset navigation bar in UiPath Communication Mining?

A. Train models using unsupervised learning.
B. View, save, and modify dataset model versions.
C. Access detailed, quervable charts, statistics, and customizable dashboards.
D. Monitor model performance and receive recommendations.

Answer: C

NEW QUESTION # 172
What information is required when creating a data labeling session?

A. Dataset and Al Center project.
B. Data labeling name, dataset. and Al Center project.
C. Data labeling session name and dataset.
D. Data labeling name, language, and number of documents.

Answer: C

Explanation:
When creating a data labeling session in UiPath AI Center, the key pieces of information required are:
* The data labeling session name: A unique identifier for the session.
* The dataset: The data that will be used in the labeling session.
For more details, refer to:
* UiPath AI Center Documentation: Data Labeling Sessions

NEW QUESTION # 173
What is one best practice when designing a UiPath Communications Mining label taxonomy?

A. Each label should overlap sliqhtlv with a few distinct others so we ensure 100% coveraqe.
B. Each parent label should have at least 3 children labels to ensure specificity.
C. Each label should be identifiable from the text of the individual verbatim (not thread) to which it will be applied.
D. Each label should include customer experience/sentiment analysis in its coverage.

Answer: C

Explanation:
A label taxonomy is a hierarchical structure of concepts that you want to capture from your communications data, such as emails, chats, or calls. Each label represents a specific concept that serves a business purpose and is aligned to your objectives. A label taxonomy can have multiple levels of hierarchy, where each child label is a subset of its parent label. For example, a parent label could be "Product Feedback" and a child label could be "Product Feature Request" or "Product Bug Report". A label taxonomy is used to train a machine learning model that can automatically classify your communications data according to the labels you defined1.
One of the best practices for designing a label taxonomy is to ensure that each label is clearly identifiable from the text of the individual verbatim (not thread) to which it will be applied. A verbatim is a single unit of communication, such as an email message, a chat message, or a call transcript segment. A thread is a collection of related verbatims, such as an email conversation, a chat session, or a call recording. When you train your model, you will apply labels to verbatims, not threads, so it is important that each label can be recognized from the verbatim text alone, without relying on the context of the thread. This will help the model to learn the patterns and features of each label and to generalize to new data. It will also help you to maintain consistency and accuracy when labelling your data2.
References: 1: Communications Mining - Taxonomies 2: Communications Mining - Label hierarchy and best practice

NEW QUESTION # 174
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