Classifier Transformation Example
You can use a classifier model and a Classifier transformation to categorize email messages based on the text that they contain.
For example, you are a data steward in the customer support center of a software manufacturer. You review the email messages that the support center receives from customers. The organization has customers in many countries, and the support center receives emails in many languages. You decide to sort the emails by language, so that you can send each email to the department that can best reply to the customer.
To sort the emails, perform the following steps:
- 1. Write the email messages to a single file or a database table.
- 2. Create a data object in the Model repository that reads the file or the database table.
- 3. Create data objects in the Model repository for each language that a message uses.
- 4. Create a classifier model that contains sample text for each language.
Note: You can use sample data from the email messages data as source data for the model.
- 5. Add the classifier model to a reusable Classifier transformation.
- 6. Configure a mapping to apply the Classifier transformation to the message data.
To configure the mapping, perform the following steps:
- - Add the Classifier transformation and the data objects to the mapping.
- - Connect a Classifier transformation input port to the source data object.
- - Connect the Classifier transformation output ports to the target data objects.
When you run the mapping, the Classifier transformation analyzes the email messages and writes the email text to the correct data target. You can share the data targets with the team members in each department.