When learning the mapping for columns, the user trains the engine on how the data from the extracted lines must be mapped to the user's table data.
For primary lines, this mapping can be defined differently for different line classes. For example, if a user learned two different line samples that went to two different lines classes internally in one document, the user can then map “Unit Price” in the document to the “Unit Price” data column and the “Total Price” to the “Total Price” for the first line sample. For all lines of the second line type, the user can map “Unit Price” to “Total Price” and “Total Price” to “Unit Price.” For the next document, the Brainware Table Extraction engine will always use mapping rule #1 for the lines classified to the first line type and mapping rule #2 for the lines classified as the second line type.
If you have several Brainware Table Extraction tables in one class, the learnset is shared between these tables. In other words, if you used interactive learning for one Brainware Table Extraction table, cross-document learning, which happens if the system added the document to the learnset after document validation, is applied for all Brainware Table Extraction tables in the document.