Form Type (Node Type)
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two_pager Form Types represent trained variations of a description Document Type. These nodes store machine learning training data for Lexical and Visual document classification methods.
Each document trained will create (or supplement) a child Form Type of its assigned Document Type. This is where all the training weightings for the extracted text features reside for Lexical document classification. Each page of the document is represented by Page Types, which are its children.
Glossary
Document Type: description Document Type nodes represent a distinct type of document, such as an invoice or a contract. Document Types are created as child nodes of a stacks Content Model or a collections_bookmark Content Category. They serve three primary purposes:
- They are used to classify documents. Documents are considered "classified" when the folder Batch Folder is assigned a Content Type (most typically, a Document Type).
- The Document Type's data_table Data Model defines the Data Elements extracted by the Extract activity (including any Data Elements inherited from parent Content Types).
- The Document Type defines all "Behaviors" that apply (whether from the Document Type's Behavior settings or those inherited from a parent Content Type).
Form Type: two_pager Form Types represent trained variations of a description Document Type. These nodes store machine learning training data for Lexical and Visual document classification methods.
Lexical: "Lexical" is a Classify Method that classifies folder Batch Folders based on the text content of trained document examples. This is achieved through the statistical analysis of word frequencies that identify description Document Types.
Machine: computer Machine nodes represent servers that have connected to the Grooper Repository. They are essential for distributing task processing loads across multiple servers. Grooper creates Machine nodes automatically whenever a server makes a new connection to a Grooper Repository's database. Once added, Machine nodes can be used to view server information and to manage Grooper Service instances.
Visual: "Visual" is a Classify Method that uses image analysis instead of text data to determine the description Document Type assigned to a folder Batch Folder during classification. Instead of using text-based extractors, an "Extract Features" IP Command in an perm_media IP Profile is used to collect image-based data from a Batch Folder's image(s). This image-based data is compared against that of previously trained document examples of each Document Type to classify the Batch Folder.