communications-mining
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- Getting started
- Balance
- Clusters
- Concept drift
- Coverage
- Datasets
- General fields (previously entities)
- Labels (predictions, confidence levels, hierarchy, etc.)
- Models
- Streams
- Model Rating
- Projects
- Precision
- Recall
- Reviewed and unreviewed messages
- Sources
- Taxonomies
- Training
- True and false positive and negative predictions
- Validation
- Messages
- Administration
- Manage sources and datasets
- Understanding the data structure and permissions
- Create a data source in the GUI
- Uploading a CSV file into a source
- Create a new dataset
- Multilingual sources and datasets
- Enabling sentiment on a dataset
- Amend a dataset's settings
- Delete messages via the UI
- Delete a dataset
- Delete a source
- Export a dataset
- Using Exchange Integrations
- Preparing data for .CSV upload
- Model training and maintenance
- Understanding labels, general fields and metadata
- Label hierarchy and best practice
- Defining your taxonomy objectives
- Analytics vs. automation use cases
- Turning your objectives into labels
- Building your taxonomy structure
- Taxonomy design best practice
- Importing your taxonomy
- Overview of the model training process
- Generative Annotation (NEW)
- Dastaset status
- Model training and annotating best practice
- Training with label sentiment analysis enabled
- Train
- Introduction to Refine
- Precision and recall explained
- Precision and recall
- How does Validation work?
- Understanding and improving model performance
- Why might a label have 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
- Licensing information
- FAQs and more
Communications Mining User Guide
Last updated Nov 19, 2024
Applying labels
User permissions required: ‘View Sources’ AND ‘Review and annotate’.
Apply a single label
- Navigate to Discover or Explore
- Click 'Add label +' or just '+' (for messages that have predictions) underneath the message to either select labels previously created within this taxonomy or use the text box to create new labels
- Click enter or the tick icon to apply the label, or if sentiment analysis is enabled click either of the icons to apply the
label with positive or negative sentiment
Note:
The format for label structure should be one of the following:
- [Standalone Parent / Root Label]
- [Parent / Root Label] > [Leaf Label]
- [Parent / Root Label] > [Branch Label] > [Leaf Label]
We do not recommend having 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.
Apply labels in bulk
Applying labels to groups of messages can massively speed up the annotating process:
- Navigate to Discover – you can use either the cluster functionality or search
- Use the button to either select previously created labels or use 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 double click to apply these labels to the messages you have selected
- Please Note: all messages will automatically be selected, clicking the toggle button on the bottom right-hand corner of a message will de-select it
Next to the button are three other buttons:
| - Hide the labels currently applied to the messages shown | |
| - Invert your selection so selected messages become de-selected and vice versa | |
| - De-select or select all messages |
