Abstract: The system is configured to create a generalized document automation framework that captures relevant data from documents based upon replicating historical human actions associated with a document. The system may use machine vision and natural language processing to match a new document to a document that was already human extracted in an existing corpus. This is accomplished by comparing both visual elements and textual elements. This match can be verified by statistical approaches by comparing the match metrics across multiple documents. After the match has been found and verified, the system then uses the historical extractions from the historical document and maps the extractions to similar regions in the new document based upon again both visual and text commonalities between documents. Data is then extracted from these regions of interest in the new document, sanity checked for data integrity against historical data, and then passed downstream for processing.

Abstract: The system is configured to create a generalized document automation framework that captures relevant data from documents based upon replicating historical human actions associated with a document. The system may use machine vision and natural language processing to match a new document to a document that was already human extracted in an existing corpus. This is accomplished by comparing both visual elements and textual elements. This match can be verified by statistical approaches by comparing the match metrics across multiple documents. After the match has been found and verified, the system then uses the historical extractions from the historical document and maps the extractions to similar regions in the new document based upon again both visual and text commonalities between documents. Data is then extracted from these regions of interest in the new document, sanity checked for data integrity against historical data, and then passed downstream for processing.

Abstract: The system is configured to create a generalized document automation framework that captures relevant data from documents based upon replicating historical human actions associated with a document. The system may use machine vision and natural language processing to match a new document to a document that was already human extracted in an existing corpus. This is accomplished by comparing both visual elements and textual elements. This match can be verified by statistical approaches by comparing the match metrics across multiple documents. After the match has been found and verified, the system then uses the historical extractions from the historical document and maps the extractions to similar regions in the new document based upon again both visual and text commonalities between documents. Data is then extracted from these regions of interest in the new document, sanity checked for data integrity against historical data, and then passed downstream for processing.

Abstract: Devices, methods and systems are disclosed herein to describe a document element indexing system which efficiently organizes different files or the constituent parts of different files into an index, thereby allowing users to easily and efficiently access, annotate and/or review the desired information. The indexing system may be applied to organize components of homogeneous and/or heterogeneous file types.

Abstract: A system for verifying and correcting errors after translation of printed text into machine-readable text. The system includes a memory for storing formulas defining relationships between data fields. A processor evaluates the formulas according to data values associated with the data fields to determine whether the formulas evaluate as truthful statements. The processor marks the data fields of the formulas as unverified or as verified based upon this evaluation. The system also uses the processor to calculate a determined value for data fields in an attempt to correct errors in the translation of the printed text into machine-readable text. If different determined values are calculated for the same data field, based upon different formulas, the data field is marked as uncertain. The system iterates based upon the marking of the data fields of the formulas as verified or unverified and as uncertain or not uncertain.

Abstract: A system for verifying and correcting errors after translation of printed text into machine-readable text. The system includes a memory for storing formulas defining relationships between data fields. A processor evaluates the formulas according to data values associated with the data fields to determine whether the formulas evaluate as truthful statements. The processor marks the data fields of the formulas as unverified or as verified based upon this evaluation. The system also uses the processor to calculate a determined value for data fields in an attempt to correct errors in the translation of the printed text into machine-readable text. If different determined values are calculated for the same data field, based upon different formulas, the data field is marked as uncertain. The system iterates based upon the marking of the data fields of the formulas as verified or unverified and as uncertain or not uncertain.

Abstract: Devices, methods and systems are disclosed herein to describe a document element indexing system which efficiently organizes different files or the constituent parts of different files into an index, thereby allowing users to easily and efficiently access, annotate and/or review the desired information. The indexing system may be applied to organize components of homogeneous and/or heterogeneous file types.

Abstract: Systems and methods for discouraging unauthorized duplication of storage media are described. A client device is connectable to a network which is connected to a server device. The storage media may contain one or more data files stored on the storage media. The data files are capable of being read by a storage media reader contained in or connected to one of the client devices. The client device may receive updated network data from a server device as a result of using the storage media containing the data files. To prevent the downloading of the updated network data to more than one client after unauthorized duplication of the storage media, an identification number stored on the storage media is transmitted to the server device wherein only the last client device that transmitted the identification number to the server device in time should receive updated network data.