An Approach or Three to Categorization with SQL Server

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Database Information Categorization

David wrote in with a few ideas on approaching the DB tagging and categorization issues:

"Most enterprise data is in an unstructured (non-database) form, such as word processing files, spreadsheets, PDF documents, email, contracts, legislation, etc.

The enterprise needs ways of finding any of this that is pertinent to an issue.

So far, we depend on people. We depend on the right people to know that something is an issue, and we depend on their memories and the filing system they individually choose to keep track of things they believe will be needed.

My vision has four aspects to it.

1) A firm or industry makes a list of words that are important to it, and a modified word-checker program automatically notes which of these words are in a document. This is kept, along with the name and location of the document.

2) The same word-checker program lists other words that may be candidates for this important-word list. As a document is checked, the user is given this additional list and chooses which words from it to also keep in the document’s key-word list.

3) A set of rules is made for identifying the primary topic of a document, so that documents on the same topic will have a similar wording to explain the subject matter. This will help when searching for a topic.

4) An automated way will be developed to pull out significant sentences.

So, some database will keep this meta-data about documents – the document location and name, the document subject (in a way optimized for finding similar topics), the key words from the industry or company list, and other key words selected.

This would go a long way towards making non-database information available when needed."

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