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- Introduction
- Setting up your account
- Balance
- Clusters
- Concept drift
- Coverage
- Datasets
- General fields
- Labels (predictions, confidence levels, label hierarchy, and label sentiment)
- Models
- Streams
- Model Rating
- Projects
- Precision
- Recall
- Annotated and unannotated messages
- Extraction Fields
- Sources
- Taxonomies
- Training
- True and false positive and negative predictions
- Validation
- Messages
- Access Control and Administration
- Manage sources and datasets
- Understanding the data structure and permissions
- Creating or deleting a data source in the GUI
- Uploading a CSV file into a source
- Preparing data for .CSV upload
- Creating a dataset
- Multilingual sources and datasets
- Enabling sentiment on a dataset
- Amending dataset settings
- Deleting a message
- Deleting a dataset
- Exporting a dataset
- Using Exchange integrations
- Model training and maintenance
- Understanding labels, general fields, and metadata
- Label hierarchy and best practices
- Comparing analytics and automation use cases
- Turning your objectives into labels
- Overview of the model training process
- Generative Annotation
- Dastaset status
- Model training and annotating best practice
- Training with label sentiment analysis enabled
- Training chat and calls data
- Understanding data requirements
- Train
- Introduction to Refine
- Precision and recall explained
- Precision and Recall
- How validation works
- Understanding and improving model performance
- Reasons for label low average precision
- Training using Check label and Missed label
- Training using Teach label (Refine)
- Training using Search (Refine)
- Understanding and increasing coverage
- Improving Balance and using Rebalance
- When to stop training your model
- Using general fields
- Applying labels
- Reviewing messages
- Searching for messages
- Label editing
- Generative extraction
- Using analytics and monitoring
- Automations and Communications Mining™
- Developer
- Exchange Integration with Azure service user
- Exchange Integration with Azure Application Authentication
- Exchange Integration with Azure Application Authentication and Graph
- Fetching data for Tableau with Python
- Elasticsearch integration
- Self-hosted Exchange integration
- UiPath® Automation Framework
- UiPath® Marketplace activities
- UiPath® official activities
- How machines learn to understand words: a guide to embeddings in NLP
- Prompt-based learning with Transformers
- Efficient Transformers II: knowledge distillation & fine-tuning
- Efficient Transformers I: attention mechanisms
- Deep hierarchical unsupervised intent modelling: getting value without training data
- Fixing annotating bias with Communications Mining™
- Active learning: better ML models in less time
- It's all in the numbers - assessing model performance with metrics
- Why model validation is important
- Comparing Communications Mining™ and Google AutoML for conversational data intelligence
- Licensing
- FAQs and more
Communications Mining user guide
Last updated Aug 11, 2025
Note: You must have assigned the Source - Read
and Dataset - Review permissions as an Automation Cloud user,
or the View sources and Review and annotate
permissions as a legacy user.
- Navigate to the Discover or Explore tabs.
- Select Add label +, or the
plus sign
+for messages that have predictions, for the message to either select labels previously created within this taxonomy, or use the text box to create new labels. - Enter the name of the label.
- Hit Enter or select tick
icon to apply the label. If sentiment analysis is enabled, select either of the
icons to apply the label with positive or negative sentiment.
Note: The label structure format should
be one of the following:
- [Standalone Parent / Root Label]
- [Parent / Root Label] > [Leaf Label]
- [Parent / Root Label] > [Branch Label] > [Leaf Label]
You are not recommended to have more than three levels in a label hierarchy, as it becomes increasingly complex for users to train. In certain cases, this might be required, but it should not be considered best practice.
Applying labels to groups of messages can massively speed up the annotating process:
- Navigate to Discover, where you can use the Cluster or Search functionality.
- Select the Add label + button to add previously created labels, or select the text box to create new labels.
- Add as many labels as necessary to fully annotate the messages.
- When you have fully annotated the
messages, select Apply labels to apply these labels to the selected
messages.
Note: All messages will be selected automatically. Selecting the toggle button on a message will deselect it.
On the same page, you can also find the following buttons:
| Hide label
| Hide the labels currently applied to the messages shown. |
| Invert selection | Invert your selection so selected messages become deselected and vice versa. |
| Select or deselect messages
| Deselect or select all messages. |
