Systems for generating a USPTO office action response document based on an input USPTO Office Action document. A method implementation for constructing the USPTO office action response traverses a ruletree that has been dynamically formed from user answers to successive questions based on characteristics of the USPTO Office Action document. The ruletree comprises a first set of data items that pertains to an HCI and the ruletree further comprises a second set of data items that pertain to the target USPTO office action response document. Correspondence between the set of user answers to questions and passages in the USPTO office action response document are maintained in the ruletree. The ruletree expands and contracts during user interaction. To generate the USPTO office action response document, the ruletree is traversed in a sorted order, where traversal of a node generates a passage or passages in the generated USPTO office action response document.

Systems for generating a USPTO office action response document based on an input USPTO Office Action document. A method implementation for constructing the USPTO office action response traverses a ruletree that has been dynamically formed from user answers to successive questions based on characteristics of the USPTO Office Action document. The ruletree comprises a first set of data items that pertains to an HCI and the ruletree further comprises a second set of data items that pertain to the target USPTO office action response document. Correspondence between the set of user answers to questions and passages in the USPTO office action response document are maintained in the ruletree. The ruletree expands and contracts during user interaction. To generate the USPTO office action response document, the ruletree is traversed in a sorted order, where traversal of a node generates a passage or passages in the generated USPTO office action response document.

A computer-implemented method, apparatus and program product use the spatial locations of words identified in an unstructured document to both reconstruct lines in the unstructured document and vertically partition the unstructured document. Key/value pairs may then be generated from one or more of the reconstructed lines by using one or more words to one side of the vertical partition as keys and using one or more words to the other side of the vertical partition as values.

A computer-implemented method, apparatus and program product use the spatial locations of words identified in an unstructured document to both reconstruct lines in the unstructured document and vertically partition the unstructured document. Key/value pairs may then be generated from one or more of the reconstructed lines by using one or more words to one side of the vertical partition as keys and using one or more words to the other side of the vertical partition as values.

It is provided a computer-implemented method for recording one or more documents. Each document comprises at least one word. The method comprises providing one or more documents forming a first set of documents. The method comprises dividing each document of the first set into one or more blocks. The method comprises creating a directed graph representing relationships established between the blocks of documents of the first set. The method comprises providing at least one block from a previous division of each document of a second set of documents. The method comprises merging the directed graph created for the first set with another directed graph previously created for the second set and taking account of at least one established relationship. The method improves the recording of the sets of documents.

The present disclosure relates to style determination method, apparatus, device, storage medium and program product. The method comprises: acquiring a style file associated with a child element, wherein the style file associated with the child element comprises one or more of: a style file corresponding to the child element, a style file corresponding to a root element of the child element, and a style file corresponding to an element on an element chain between the child element and the root element; acquiring first style information corresponding to the child element from at least one or more of the style files; determining a target style information corresponding to the child element based on at least one or more the first style information.

The present disclosure relates to style determination method, apparatus, device, storage medium and program product. The method comprises: acquiring a style file associated with a child element, wherein the style file associated with the child element comprises one or more of: a style file corresponding to the child element, a style file corresponding to a root element of the child element, and a style file corresponding to an element on an element chain between the child element and the root element; acquiring first style information corresponding to the child element from at least one or more of the style files; determining a target style information corresponding to the child element based on at least one or more the first style information.

A system for electronic data interchange (EDI) management includes a memory for storing the EDI document data and a machine learning model representing a set of features of EDI documents and a corresponding status. The system further includes a processor and a non-transitory computer readable medium storing instructions for: accessing an EDI file, the EDI file comprising envelope metadata for an envelope and a first EDI document; and translating the EDI file into a first translated EDI document containing the envelope metadata and a set of EDI document data extracted from the first EDI document, the first translated EDI document formatted according to a hierarchical structure comprising attributes translatable into features processable by the machine learning model to determine a status of the first EDI document.

A system for electronic data interchange (EDI) management includes a memory for storing the EDI document data and a machine learning model representing a set of features of EDI documents and a corresponding status. The system further includes a processor and a non-transitory computer readable medium storing instructions for: accessing an EDI file, the EDI file comprising envelope metadata for an envelope and a first EDI document; and translating the EDI file into a first translated EDI document containing the envelope metadata and a set of EDI document data extracted from the first EDI document, the first translated EDI document formatted according to a hierarchical structure comprising attributes translatable into features processable by the machine learning model to determine a status of the first EDI document.

Embodiments disclosed herein include systems and methods for generating and editing digital documents, and applying electronic signatures to the documents. The system further performs forensic operations on digital documents for determining the authenticity of the document data or metadata and validating the status of document. The forensic operations may include, for example, security operations, audit trail analysis, and authenticity/verification analysis, which the system performs on an input document being scrutinized for authenticity and a master digital document purportedly corresponding to the input digital document. The system may apply a machine-learning architecture to identify discrepancies otherwise imperceptible to humans or to speed the review process. The system may generate a report for the user who submitted the forensics request indicating the results of the forensic operations. The available forensics operations and level of information about the master digital document are tailored to permissions afforded to the submitting-user.