Create your own email log type
Follow a simple naming convention for the top-level text analytics module to create the new email type. You have already seen similar naming conventions being used by the out-of-the-box log types. Following this naming convention is important since it enables the new email log type to plug and play with the Extraction application and the rest of the applications in the Accelerator.
In the next article in this series, you will see how this new log type can plug and play during indexing and searching.
First you need to create a log type called email. Then, you need to create the top-level text analytics module called extractor_email.
Perform the following steps.
- Under the AQL folder, create a new folder called email.
- Download email.aql. You can get it from the code_and_data.zip file in the Download section. This contains the AQL rules for the email log type.
- Import the email.aql file into the email folder.
- Under the AQL folder, create a new folder called extractor_email.
- Download extractor_email.aql from the code_and_data.zip file in the Download section. This contains the top-level module to include the email rules from email.aql.
- Import the extractor_email.aql file into extractor_email folder. The new AQL rules are now in place for you to run them on email data.
- Run the MDAExtractApp project again using the
Text Analytics configuration, this time selecting
extractor_email for the module, as shown in
Figure 10. Run project using email log type
- View the results in Annotation Explorer. You can also double click on the entries in the Annotation Explorer to see the results in context of the email data.
- You will notice that the To and From fields from the email data
are extracted successfully, as shown in Figure 11.
Figure 11. See results of running the email log type