Want to be better organized to be more effective? Classifying your documents is an important step to take. At work, you may have folders filled with papers pertaining to a certain topic neatly filled away into a labeled folder. Even on your computer you classify different documents and place them into their correct “folders.”
Intelligent Document Understanding takes these differences in documents and sorts them into four different classification methods.
- Symbolic: The easiest and most accurate method, which usually features barcodes. It typically is used with paper or fax documents but not e-mail.
- Graphics-based document analytics: This method classifies the documents based on their appearance but not what the text actually says. This is typically used for invoices or semi-structured documents.
- Graphics-and text-based keyword combined: This process lacks much flexibility, but can classify a bit more than the previous method. It looks at the graphics (appearance) and can see that it is an invoice; however it also will pick up on keywords in the document such as “car repair” and place it into the correct folder.
- Full, text-based document analytics: This is the newest method which also is the most complex yet versatile of the four. It can classify all text-based documents which range from paper, e-mails and social media.
There are also three “classes” of documents in which the different methods follow to arrange the documents.
- Unstructured: Simple and no variability, typically documents that have an unknown page layout with variable content. Typically these are correspondence or mailrooms.
- Semi-Structured: These are documents such as invoices, which are the same types of document but vary with information. These typically have an unknown page layout with tabular data.
- Structured: These documents are very complex and vary a lot. They have a fixed page layout and consistent, defined content. Examples of structured documents are applications, benefit forms or checks.
Do you have any questions about document classification? Read more about this topic in our whitepaper.
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