Rules-Based Approach: Difference between revisions
Configadmin (talk | contribs) Created page with "This approach uses regular expression pattern matching to find key words, phrases, or other lines of text in order to identify and classify a document...." |
Dgreenwood (talk | contribs) No edit summary |
||
| Line 1: | Line 1: | ||
This approach uses [[ | This approach uses [[Data Extractor]]s to find key words, phrases, or other text-based information in order to identify and classify a document (assigning a '''[[Document Type]]''' to a document). For example, a document with a centered header of "Purchase Report" might be classified as a "Purchase Report" '''Document Type''' with this approach. One could build a [[Data Type]] extractor using regular expression to match the phrase "Purchase Report" centered at the top of a document to identify it. Once set on the '''Document Type''', if the extractor returned a result on a document, it would be classified as a "Purchase Report" '''Document Type'''. | ||
These "rules" are set using the '''''Positive Extractor''''' and '''''Negative Extractor''''' properties of a '''Document Type''' object in a '''[[Content Model]]''' | |||
Revision as of 15:11, 6 October 2020
This approach uses Data Extractors to find key words, phrases, or other text-based information in order to identify and classify a document (assigning a Document Type to a document). For example, a document with a centered header of "Purchase Report" might be classified as a "Purchase Report" Document Type with this approach. One could build a Data Type extractor using regular expression to match the phrase "Purchase Report" centered at the top of a document to identify it. Once set on the Document Type, if the extractor returned a result on a document, it would be classified as a "Purchase Report" Document Type.
These "rules" are set using the Positive Extractor and Negative Extractor properties of a Document Type object in a Content Model