Category Summaries are essential for training AI classifiers to accurately distinguish and classify text within workitems. By uploading examples of text, the AI learns to identify and categorize similar incoming workitems. This automated classification improves the efficiency and accuracy of routing text-based workitems, such as SMS, emails, WhatsApp messages, and chats.
Creating a Category Summary
Search for the Category Summary icon on the options menu. Click Plus (+) and fill out the required information.
Information Tab
|
Field Name |
Description |
|
Name |
The name of the Category Summary. |
|
Description |
A description of the Category Summary. |
Categories Tab
The Categories Tab will be where you can select the Categories used in the classifier (the target labels).
Category Summary Tab
The Category Summary Tab is where you upload the CSV with examples first to train the classifier. Each Category Summary can have up to two machine learning models, which can be switched between, so there is always an active and a training model. The buttons allow you to toggle between them.
NOTE: You must disable the first model before enabling the second one.