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Configuring text extraction analysis

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Configure text extraction analysis by specifying tags, keywords, entity extraction models, and pattern extraction rules. Use tags and keywords to mark specific terms and their synonyms that you want to identify in the analyzed text. Text and pattern extraction models help to identify various types of named entities.

Text extraction analysis helps you track the activity of your customers and competitors or discover the products and features that customers comment on most often.

  1. In the Records navigation panel, click Decision Text Analyzer .

  2. Open the Text Analyzer rule that you want to configure.

  3. Perform any of the following actions:

    • To detect the most relevant words or phrases in a document to, for example, create word clouds or perform a faceted search, in the Text extraction section, select the Enable auto-tag extraction check box and perform one of the following actions:
      • To detect all significant tags in the document, click Detect all tags.
      • To detect a specific number of tags in the document, click Detect top N tag(s) and specify the number of tags that you want to detect.
    • To summarize the text that you analyze, select the Enable summarization check box and specify the compression ratio.
      The compression ratio is specific to your use case. For example, to create very short summaries of large bodies of text, you can specify the compression ratio as 1% to extract only the few most information-rich sentences.
    • To extract named entities from text, select Enable text extraction.
  4. If you selected the Enable text extraction, select an entity model by performing the following actions:

    1. Click Add extraction model.

    2. In the Extraction model field, provide the name of the name of the entity model to use for named entity extraction.

    3. Optional:

      To choose the detectable entity types in the model, select or clear the check box next to the applicable entity type.

    4. Click Submit to confirm your settings.

  5. Click Save to confirm your settings.

  • Text extraction analysis

    Text extraction analysis is the process of extracting named entities from unstructured text such as press articles, Facebook posts, or tweets, and categorizing them. Typically, a named entity is a proper noun that falls into a commonly understood category such as a person, organization, or location. An entity can also be a Social Security number, email address, postal code, and so on.

  • Testing Text Analyzer rules

    You can test the performance of a Text Analyzer rule after you configured that rule to perform natural language processing tasks that fulfill your business requirements.

  • Configuring advanced text analytics settings

    Configure language detection settings, enable spell checking, and control how the text is categorized, based on various criteria.

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