Importing a taxonomy for keyword-based topic detection
After you create a topic 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.
- Create a
.csv,.xls, or.xlsxfile with defined topics and corresponding keywords. For further information, see Requirements and best practices for creating a taxonomy for rule-based classification analysis. - Create a keyword-based topic model by specifying the model name, language, and corresponding ruleset. For more information, see Setting up a keyword-based topic model.
- In the Taxonomy workspace, click .
- In the Import taxonomy dialog box, click Choose
file, and then select the
.csvor.xlsxtaxonomy file. - Click Import.
- 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.
- Optional: To test your taxonomy, select .
Tip: 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. - Save the taxonomy by clicking Save.You can use the taxonomy as part of a machine learning topic model or directly in Text Analyzers to perform keyword-based topic detection.
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