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Before You Index > Enrich Your Content > Document Tagging

# Document Tagging

Document Tagging is the general process of adding extra information to documents. It includes static additions to the documents (for example, adding information from Eduction into the document) or more dynamic information (for example, marking a document for further analysis or workflow).

You can use document tagging to:

- store the result of indexing steps (Categorize Documents, Eduction, Sentiment Analysis) for later retrieval.

- build interactive applications on top of data stored in IDOL.

## Query with Tags

Tags have various uses for querying.

- If the tag is a short piece of text (for example, a category or country), you might want to display a list of the tags that are present, and allow users to pick a tag to use to filter the results. See Parametric Search .

- If the tag is a long value (for example, a phone number), or the tag field contains a large number of possible values, you might want to search for a value in the field. See Field Search.

- If the tag contains a wide range of long possible values (for example, addresses), you might want to be able to use a basic search. See Basic Queries.

In general, filtering is the most efficient use. A full text index for entity fields might take up a lot of index space, which can reduce query speeds. You should only use this option in cases where you can get the most value from the text by being able to search it for stemmed values and similar terms.

## Use Tags in Other Processes

You might be able to use your tags in other processing that you apply before you index the documents. You might use the tags to:

- categorize documents.

- match the documents to information you store about user interests, and use it to alert users to content that matches their interests.

- use the tag data to analyze the content and decide whether to index it at all.

- use the tag as a flag to route the document for other workflow processes.

You might use Eduction to extract country names from documents before you index them, and then add the country name to a field. You might then perform categorization to add each document to the category for each country that it includes.

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