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Understanding the information contained within text (unstructured information) from a analytic perspective requires extracting information such as the list of people or companies mentioned in an article, or the sentiment of a product review. Generally, this can be thought of as structuring the unstructured. By retrieving this information from text and putting into metadata fields, analyses can be performed that were previously impossible.

For example, if you wanted to count the number of published news articles related to your customers, you could JOIN a news table in AIE against your customer table in AIE using the customer_name field from the customer table and the derived company field from the news table.  You could also create a facet on the derived company field to filter news articles by company.

Entity extraction is one technique for structuring the unstructured, but there are a variety of techniques AIE supports for extracting information from text. These techniques are called text analytics.  The sections below guide you through how to apply these different techniques to derive deeper understanding from unstructured information and how to use the derived information for blended structured and unstructured information analytics with AIE. 

Language processing is often a prerequisite for many text analytic approaches and is sometimes designated as a type of text analysis. From a documentation perspective, Language processing is part of the Configuring Languages in Attivio.

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