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)
- Understanding the status of your dataset
- 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
Searching for messages
Communications Mining User Guide
Last updated Nov 7, 2024
Searching for messages
User permissions required: ‘View Sources’ AND ‘View Labels’.
You can use search in either Explore or Discover (switching from cluster mode via the dropdown menu) to search for messages containing specific terms or phrases. The platform highlights occurrences of your search terms within the messages (as shown below).
Search in Explore vs. Discover
- The key difference between searching in Discover and Explore, are that in Discover you can annotate search results in bulk (just like annotating clusters), whilst in Explore you annotate them individually
- Unlike Discover, however, Explore returns an approximate total number of messages that match your search term (as shown below) - this can be very useful when trying to gauge how many examples there may be in your dataset before creating a label, if there are terms very closely linked to the label concept
Example search query in Explore
Example search query in Discover