Communications Mining
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    • About the Communications Mining activities
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  • Communications Mining Activities
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Communications Mining Activities
Last updated Jun 28, 2024

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Activities

Get Stream Results and Get Attachments

The Communications Mining Activities package allows you to consume results from the Communications Mining streams. In this tutorial you can see an example of the invoice submissions process.

You are guided on how to consume a Communications Mining stream, identify invoice submission requests and download the associated attachments from the communications.

Key Concepts

  • Results - A representation of a communication that is returned from the Communications Mining stream. The results contain two key properties:
    • comment - contains all the information about the communication that was uploaded to the platform, such as: the subject, body, and time stamp of the communication.
    • prediction - contains the set of predictions that are returned against that communication. Within this property you can find extractions and fields.
  • Extraction - A prediction related to a specific instance of a request associated with a label, such as an Address Change request, and the fields linked to that request: Address Line 1, Town/City, Zip code. For every label you can predict multiple extractions on each message. Each extraction has an associated Occurrence Confidence and an Extraction Confidence.
  • Field - A data point extracted as a value from a message.

    A field can have the following types:

    • general field (not associated with any labels).
    • extraction field (linked to a specific label and required to process requests associated with that label).
  • Occurrence Confidence - A model's confidence level about the presence of a specific extraction instance. For instance, how certain the model is about a second Change of Address request in the message.
  • Extraction Confidence - A model's confidence level that an individual extraction is correctly extracted - i.e. the extraction is correctly identified, and all of the fields are correctly identified and associated with the correct extraction.
  • Thresholding - Each label prediction returned from a stream contains a thresholds property. This property contains the list of thresholds that have been surpassed for the given prediction. Currently, the threshold that you configure on the stream is called a stream.
Prerequisites
  • Access to Communications Mining.
  • An exchange integration configured and populating a source.
  • A trained dataset based on this source.
  • A stream configured on this trained dataset.
Follow the steps below, to consume stream Results and obtain attachments.

Step 1 - Connect to your stream

Within a Studio project, drag in the Get Stream Results activity from the Communications Mining activities library and select your stream.


Step 2 - Start looping your stream results

Drag in a For Each loop and start iterating the Results field of the variable output from the Get Stream Results activity.


Step 3 - Determine if the result is an Invoice Submission

Within your For Each loop, add an If statement, and check if the Invoice Submission request has been detected with the following expression: result.Prediction.ContainsLabelExtraction("Invoice Submission")


Note: You can also access any field values that you have configured for this label with the result.Prediction.GetLabelExtractions("Invoice Submission")(0).GetField("Invoice Date") expression.

Step 4 - Download the attached invoice

Drag in the Get Attachment activity to the Then section of your if statement. You can then retrieve the attachment reference with the following expression: result.Comment.GetAttachmentsByType("pdf")(0).AttachmentReference.


Note: This expression assumes that at least one PDF attachment exists. Check in production that this is the case.

Step 5 - Pass the attachment to Document Understanding

You can now use the downloaded attachment and pass it Document Understanding:



Step 6 - Advance the stream

Once you have processed all of the results in the stream batch, use the Advance Stream activity to advance the stream to retrieve more results:


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