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Importing a taxonomy for keyword-based topic detection

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After you create a topic detection model, import a taxonomy that contains defined topics and keywords for topic detection. Based on the keywords, topic detection assigns topics to the analyzed piece of text.

  1. Create a .csv, .xls, or .xlsx file with defined topics and corresponding keywords. For more information, see Requirements and best practices for creating a taxonomy for rule-based classification analysis.
  2. Create a keyword-based topic detection model by specifying the model name, language, and corresponding ruleset. For more information, see Setting up a keyword-based topic detection model.
  1. In the Taxonomy workspace, click Actions Import .

  2. In the Import taxonomy dialog box, click Choose file, and then select the .csv or .xlsx taxonomy file.

  3. Click Import.

  4. To detect child topics only when the corresponding parent topic is detected, for the parent topic, select the Match child topics only if the current topic matches check box.

  5. Optional:

    To test your taxonomy, select Actions Test .

    Always test your taxonomy on a number of text samples to determine whether it accurately assigns topics. Depending on the results, you might refine your taxonomy, for example, by increasing the number of Should words to accommodate additional use cases, or by adding Not words to help differentiate between similar categories.
  6. Save the taxonomy by clicking Save

    You can use the taxonomy as part of a machine-learning topic detection model or directly in Text Analyzers to perform keyword-based topic detection.

  • Creating keyword-based topic detection models

    Efficiently connect your customers with the right consultant without having to provide training data to the topic detection model. Instead, you can use a list of topic-specific keywords to train the model.

  • Detecting the topics of text fragments

    Efficiently categorize and rout customer inquiries to the corresponding customer service consultant with topic detection. Topic detection scans a piece of text and determines the underlying topic, and then automatically assigns the text to a predefined category.

  • Analyzing natural language

    Effortlessly analyze and extract meaningful information from large volumes of text with the use of text analytics. Based on your findings, you can further improve business performance and customer experience.

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