- Getting Started
- 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
- Export a dataset
- Using Exchange Integrations
- Preparing Data for .CSV Upload
- Model Training and Maintenance
- Understanding labels, entities 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 labelling 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 Analytics & Monitoring
- Automations and Communications Mining
- FAQs and More
Streams
A 'stream' (formerly known as a 'trigger') in the platform is essentially a tool for automatically creating a queue of messages, which satisfy specific label or metadata conditions.
Streams are frequently used in the platform to facilitate automated processing of requests, with the platform acting as the interpreter of an unstructured communication. The platform understands and adds structure to the communication and makes it available downstream for processing.
This queue is made available to downstream applications via the Communications Mining API endpoints. The outputs from the API are machine readable objects in JSON format, containing all of the associated metadata, message text, and the associated labels as structured data points.
For an explanation on how to set up or update a stream, please see here.
