Abstract: An automated method for assembling common commercial documents such as invoices, bills of lading and purchase orders placed in multipage files containing multiple documents without separators is described. The method is applicable in the presence of attachments and utilizes training data consisting of fields of interest and their locations in documents together with invariant fields frequently present in documents.

Abstract: A completely automated method for classifying electronic images of commercial documents such as invoices, bills of lading, explanations of benefits, etc. is based on the layout of the documents. A document is classified as belonging to a class of similarly laid out images if its distance, determined by a set of pre-defined metrics, to any of the template layouts from the same class of template layouts does not exceed a certain user-defined threshold. Alternatively, if the sum of distances from a given image to several template layouts from the same class does not exceed a user-selected threshold, the image is deemed to belong to a class of images with a specific layout.

Abstract: A completely automated method for classifying electronic images of commercial documents such as invoices, bills of lading, explanations of benefits, etc. is based on the layout of the documents. A document is classified as belonging to a class of similarly laid out images if its distance, determined by a predefined metric, to any of the templates from the same class of templates exceeds a certain user-defined threshold. Alternatively, if the sum of distances from a given image to several templates from the same class exceeds a user-selected threshold, the image is deemed to belong to a class of images with a specific layout.