Abstract: Methods and systems for transforming at least a portion of a physical document into digital data. One method includes obtaining a first plurality of data items automatically extracted from a first physical document and a validated value for a data field. The method also includes automatically identifying a first linked data item included in the first plurality of data items that is linked to the validated value and setting a physical position included in a rule to the physical position of the first linked data item. In addition, the method includes obtaining a second plurality of data items automatically extracted from a second physical document and automatically identifying a candidate data item included in the second plurality of data items based on the rule. Furthermore, the method includes automatically populating a value for the data field for the second physical document based on the candidate data item.

Abstract: Methods and systems for transforming at least a portion of a physical document into digital data. One method includes obtaining a first plurality of data items automatically extracted from a first physical document and a validated value for a data field. The method also includes automatically identifying a first linked data item included in the first plurality of data items that is linked to the validated value and setting a physical position included in a rule to the physical position of the first linked data item. In addition, the method includes obtaining a second plurality of data items automatically extracted from a second physical document and automatically identifying a candidate data item included in the second plurality of data items based on the rule. Furthermore, the method includes automatically populating a value for the data field for the second physical document based on the candidate data item.

Abstract: Systems and methods for automated document separation. The system includes a host device that is configured to communicate with one or more client devices over a network. The host device includes a splitting module, a correction module, a knowledge base, and a document store. The splitting module is configured to perform a multi-level document splitting. Pages are grouped into documents based on the sender information, the lack of sender information, and whether the sender is known. The splitting module performs an automatic correction of the initial document separation based on information stored within the knowledge base. The knowledge base is updated each time a document is processed and a user provides feedback related to whether the documents were successfully separated. Based on the success or failure of a particular document separation, the knowledge base evaluates the modifications made by a user to learn from the errors made during document separation.

Abstract: Systems and methods of recognizing a business document and creating a document signature. In one embodiment, a business document is scanned and a business document image is created. The business document image is compared to a template database. If a matching template is found, document fields are defined and extracted. If no matching document template is found, the document image is compared to a skeleton database. If a matching document skeleton in found, document fields are defined and extracted. A document skeleton is generated and then stored in the template database. If no matching document skeletons are found in the skeleton database, document fields are manually extracted. A document skeleton is then generated from the identification of static and variable strings and stored in the skeleton database. Document fields are validated after all document fields have been extracted.

Abstract: Systems and methods for automated document separation. The system includes a host device that is configured to communicate with one or more client devices over a network. The host device includes a splitting module, a correction module, a knowledge base, and a document store. The splitting module is configured to perform a multi-level document splitting. Pages are grouped into documents based on, for example, the sender information, the lack of sender information, and whether the sender is known. Following the initial separation, the splitting module performs an automatic correction of the initial document separation based on information stored within the knowledge base. The knowledge base is updated each time a document is processed and a user provides feedback related to whether the documents were successfully separated. Based on the success or failure of a particular document separation, the knowledge base evaluates the modifications made by a user to learn from the errors made during document separation.

Abstract: Systems and methods for automated processing and distribution of documents using a customized print driver. The customized print driver is accessed using a program application running on an Internet-enabled or networkable device. Unlike conventional print drivers which output print file from an application program to, for example, a laser printer, the customized print drivers combine a print file from the application program with specific processing and distribution parameters or preferences (i.e., a macro). The macro includes, among other things, preferences related to transport medium, transport options, and contact information. By combining the print file of the application program with the macro using a customized print driver, documents are able to be electronically prepared, processed, and distributed efficiently and with minimal user intervention.

Abstract: Systems and methods of recognizing a business document and creating a document signature. In one embodiment, a business document is scanned and a business document image is created. The business document image is compared to a template database. If a matching template is found, document fields are defined and extracted. If no matching document template is found, the document image is compared to a skeleton database. If a matching document skeleton in found, document fields are defined and extracted. A document skeleton is generated and then stored in the template database. If no matching document skeletons are found in the skeleton database, document fields are manually extracted. A document skeleton is then generated from the identification of static and variable strings and stored in the skeleton database. Document fields are validated after all document fields have been extracted.