449 results about "Electronic document" patented technology

The invention provides a private deployment-oriented multi-modal AI knowledge base construction system. The private deployment-oriented multi-modal AI knowledge base construction system comprises a knowledge storage module, an intelligent document loading module, a document partitioning engine module, a data enhancement engine module, a multi-language semantic vector alignment module and a private deployment module, the knowledge storage module comprises a knowledge authority management sub-module and a knowledge source management sub-module, the knowledge authority management sub-module is used for managing and storing knowledge from different sources, and the knowledge source management sub-module is used for managing electronic documents and multimedia documents; according to the method, intelligent identification, partitioning, vectorization and source file storage can be carried out on different types of electronic files, knowledge graph construction is carried out for specific fields, semantic relevance between texts and topics and key entities is fully considered, the method has wider applicability, higher robustness and controllability, the data leakage risk is effectively reduced, and the method is suitable for popularization and application. The method is suitable for enterprise sensitive data protection and personal user elastic computing power requirements.

In various examples, systems and methods are disclosed relating to displaying images in chatbot / NPC / virtual agent / digital avatar / etc. responses. A system can identify text corresponding to an image in an electronic document and can store a representation of the text in association with an identifier of the image. The system can receive an input prompt for a machine-learning model. The system can generate a response to the input prompt using the machine-learning model. The response can include the image responsive to identifying the representation of the text using a searching function and an output of the machine-learning model.

A method, a system, and a computer program product for generating a benchmarking dataset. One or more queries for generation of one or more summaries of one or more electronic documents are received. The queries are modified using one or more parameters associated with the electronic documents to generate modified queries. The electronic documents are sent to a generative artificial intelligence (AI) model. The generative AI model generates summaries of the electronic documents based on at least one of: the initial queries and the modified queries. One or more labels for the electronic documents are generated using the summaries.

A computer-implemented method of automatically generating interactive compliance controls by a server computer system to a client computing system is provided. The method includes receiving, by the server computer system, a first input from the client computing system. The first input provides an electronic rules document including a plurality of compliance rules or identifying information for the electronic rules document, and information related to an asset. The method also includes outputting, by the server computer system to the client computing system and in response to the first input, controls corresponding to the compliance rules. The controls being rephrasings of the compliance rules and generated by inputting the electronic document into a first large language model (LLM). The first LLM being pretrained by examples specifying acceptable and unacceptable control outputs for a plurality of compliance rule inputs.

A system including a media data optimization engine (MDOE) and a method for automatically creating structured data objects for media content rendered in one or more languages in an electronic document of a business entity are provided. The MDOE identifies non-textual objects including media content rendered in one or more languages in the electronic document and generates textual objects in the corresponding language(s) therefrom. The MDOE transforms the textual objects into structured data objects based on configurable criteria and generates a dynamic index-oriented object for the structured data objects specific to the business entity. The MDOE connects the structured data objects to the dynamic index-oriented object by creating linked data nodes therefrom with the dynamic index-oriented object as a core. The MDOE connects the dynamic index-oriented object with the linked data nodes to the electronic document, thereby facilitating dynamic changes to the electronic document and dynamically optimizing the electronic document.

The invention discloses an electronic document tracing method and device based on dynamic encryption and multi-modal watermarking, and relates to the technical field of information security and digital rights management. The method comprises the following steps: acquiring a PDF document uploaded by a user, encrypting the PDF document by adopting a randomly generated main encryption key, and acquiring and storing the encrypted PDF document; the content of the encrypted PDF document is analyzed, secret information is embedded into a picture in the document based on a two-dimensional discrete cosine transform algorithm, and picture watermark embedding is completed; a self-adaptive watermark embedding algorithm is adopted to embed secret information into a text in the document, and text watermark embedding is completed; related information of the checking operation is written into a block chain database; dynamically extracting watermark information from the divulged PDF document by adopting a watermark extraction algorithm; and querying a traceability database according to the extracted watermark information, and outputting a traceability result by comparing the extracted watermark information with information in a database storing various watermark information. According to the invention, the survival rate and the concealment of the watermark can be improved.

Systems, methods, and other embodiments associated with a framework for multi-entity detection, data sourcing, and processing are described. In one embodiment, a multi-entity processing method includes parsing an electronic document being processed in a processing flow for a first entity to detect that the document also concerns a second entity based on entity identifiers in the document. In response to the detection, the method determines an inter-entity agreement that governs processing between the first entity and second entity by matching attributes of the document against stored agreement data structures. The method automatically orchestrates processing of an inter-entity transaction between the first entity and the second entity by generating execution steps according to sequential and parallel dependencies specified by the inter-entity agreement. And, the method generates electronic records in a system of the first entity and a system of the second entity that reflect execution of the inter-entity transaction.

Presented herein are systems and methods of controlling access to values in electronic documents. A first service may receive an electronic document comprising a corresponding plurality of values associated with a corresponding plurality of fields to be provided to at least one of a plurality of client devices. The first service may identify, from the electronic document, a field of the plurality of fields associated with a corresponding value of the plurality of values is to be encrypted. The first service may select, from a plurality of first encryption keys, a first encryption key based on a field type of the field. The first service may generate a token using the value and the first encryption key for the field. The first service may send to a client device of the plurality of client devices, the electronic document comprising the token replacing the value associated with the corresponding field.

The invention relates to the technical field of information security, and discloses a handwriting dynamic encryption and electronic signature method based on a national secret algorithm, and the method comprises the steps: obtaining the handwriting data of a user, and carrying out the preprocessing of the data to remove noise and errors; carrying out feature extraction on the preprocessed handwriting data, extracting corresponding track features, speed features and pressure features, and generating a feature hash value of a unique identifier through a cryptographic SM3 hash algorithm; splicing and combining the feature hash value and a user private key, deriving a dynamic key through a national secret SM2 algorithm, and generating an electronic signature by using the dynamic key; an electronic signature is combined with a timestamp to form a structured signature packet, and the signature packet is hierarchically encrypted and stored in a database through a national cryptographic SM4 algorithm. According to the method and the system, the handwritten signature picture, the digital signature technology, the electronic signature technology and the biological recognition and layout file processing technology are fused, so that the safety and the reliability of electronic document signing are improved.

The invention discloses a document content generation method based on a title structuring demand and related equipment, and relates to the technical field of artificial intelligence, the method comprises the following steps: performing structured analysis on a target electronic document to extract at least one title element in the target electronic document; receiving personalized requirements input by a user for the title elements, and performing data association on the personalized requirements and the corresponding title elements; the personalized requirements are used for guiding content generation; the title elements and the personalized requirements corresponding to the data association are combined into a generation request, and the generation request is sent to an artificial intelligence model; using an artificial intelligence model to obtain generation content according to the generation request; and inserting the generated content into a position related to the corresponding title element in the target electronic document. According to the method, the document structure can be deeply understood, a user is allowed to set independent generation requirements for different title elements, a document processing scheme for batch generation and selective optimization can be realized, and the flexibility of document processing is greatly improved.

The invention belongs to the technical field of electronic document processing, and particularly relates to an electronic document standardization modeling processing system which comprises a document input preprocessing module, a format standardization conversion module, an analysis reconstruction module, a metadata extraction management module, a quality inspection correction module, an experience optimization module and a security privacy protection module. According to the application, the acceptability of documents of different sources is improved through the document input preprocessing module, it is ensured that various types of electronic documents can be processed, the problem of typesetting disorder caused by format differences is reduced through the format standardization conversion module, and the document appearance consistency is kept through accurate style mapping; the analysis precision is improved through the analysis and reconstruction module, so that the original layout and style are better reserved; through the metadata extraction management module, the document management and retrieval capability is enhanced, and meanwhile, an adjustment space is provided to adapt to requirements under special conditions.

Techniques for identifying a document layout are disclosed. In one embodiment, attribute data associated with an electronic document is accessed. A machine learning model is then applied to the attribute data. The machine learning model is configured to classify the electronic document based on the attribute data and feature sets of a plurality of document classes. Based on the document class predicted by the machine learning model, the system identifies a layout associated with the document class. The layout specifies layout elements and content types associated with the layout elements. The system extracts and stores information from the electronic document according to its content type.

The invention belongs to the technical field of product production cycle management, and particularly relates to an electronic image-text file remote multi-bin collaborative storage method based on a PLM. Comprising the steps that a 1 + N hybrid storage architecture is constructed, one center bin is deployed in an enterprise headquarter data center and stores full document metadata and latest version files, and N area bins are deployed according to geographic areas and store cache copies and incremental update data of local high-frequency access documents; the remote multi-warehouse document increment synchronization is realized through an intelligent synchronization engine, and the intelligent synchronization engine adopts a content awareness increment synchronization algorithm and a dynamic synchronization strategy based on network quality; version management is realized through a version cooperative control module, and the version cooperative control module is used for establishing a global version number mapping mechanism and a conflict resolution decision tree; cross-warehouse process automation is realized through a cross-warehouse workflow engine, and the cross-warehouse workflow engine integrates a BPM process engine and a message queue; the method can adapt to a remote network environment, and the large file synchronization efficiency is improved.

The invention discloses a method for evaluating the technical content of an electric power bidding document, which comprises the following steps of: extracting the bidding document and each bidding document from a bidding platform, and analyzing and acquiring the technical content of each bidding document through an electronic document; intercepting the content of a construction safety specification plate from the content of the technical part of each bidding document, judging whether the content contains a necessary module and whether each subide of the necessary module meets the safety specification standard, and evaluating the safety specification conformity of each bidding document; according to the evaluation result of the safety specification conformity of each bidding document, preliminarily screening out each qualified bidding document; equipment material technical parameter plate content is intercepted from technical part content of each preliminarily screened qualified bidding document, technical parameters of core equipment, materials and accessories are acquired and compared with corresponding technical parameter requirements in the bidding document, technical parameter conformity scores of each bidding document are evaluated, and ranking is generated; the bid evaluation efficiency and quality are improved, fairness and justice are ensured, and the method is suitable for bidding files of different formats.

In methods and systems for generating secure verification documents are disclosed, a processor that is associated with a multifunction print device will receive one or more source electronic document files, each of which includes content of one or more source documents, each associated with a unique content creator. The processor will cause a print engine of a multifunction device to print a plurality of verification document sheets, each of which comprises data from at least one of the source documents and includes a unique identifier (ID). After printing each verification document sheet, the processor will cause a scanner of the multifunction device to scan the verification document sheet to capture a digital image of the verification document sheet. The processor will then save the digital images of the verification document sheets to a data store.

Embodiments extract a layout from a digital image of a document, including performing an analysis of image data to identify areas of content and storing the identified areas as design elements of an electronic document template. Analyzing the image data to identify areas of interest includes testing a plurality of lines of pixels from the digital image against a background color definition to identify boundaries of a content area of interest. Content from the content area of interest is processed using a machine learning model to assign a content type for the content area of interest, where the machine learning model represents multiple types of content and is trained to assign content types to input content. The content area of interest is stored as a design element of a digital page template.

The present disclosure describes a computer-implemented method for generating certification data for an electronic document, which comprises carrying out, in a computing unit, the steps of: a) authenticating a user by means of an identity verification process, the identity verification process including carrying out at least a first authentication and a second authentication; b) receiving, from a user terminal, a status certification request associated with a file, wherein the file is stored in a database, and wherein the file includes at least the electronic document; c) transmitting, to a validating server, a verification request that includes the file and a piece of identification data associated with the user; and d) receiving, from the validating server, a piece of certification data associated with the verification request.

A method, an apparatus, and a computer-readable storage medium for searching of electronic documents. A search query is encoded to form a search vector. The search query includes at least one search term and seeks information within a plurality of electronic documents. A knowledge graph structure is generated using at least one search term. The search term is associated with at least another term in a plurality of terms in the knowledge graph structure. The search query is modified using the other term to generate a modified search vector. A response to the search query is generated based on one or more responsive document vectors retrieved from the plurality of electronic documents and that are semantically similar to the modified search vector.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating content items based on source document metadata using a generative neural network. One of the methods include: receiving, from a user, a request to generate a content item using a generative neural network conditioned on a context input, wherein the context input comprises content derived from a source electronic document; obtaining metadata associated with the source electronic document; generating a prompt for the generative neural network based on the context input and the metadata associated with the source electronic document; processing the prompt using the generative neural network to generate the content item; and providing the content item for presentation to the user.

A computer-implemented natural language processing method can include storing a criteria embedding generated from a criteria document containing natural language or otherwise unstructured text in a vector database; for each individual document in the throughput of electronic documents: generating, with a first language model, a text summary of the individual document; conducting, using retrieval augmented generation, a semantic search to identify relevant passages from the vector database based on the text summary of the individual document; generating, with a second language model, retrieval-augmented text by performing semantic textual similarity with the identified passages and the text summary of the individual document; and generating, with a third language model, a set of assessment outputs based on the text summary of the individual document and the retrieval-augmented text.

An electronic document transformation and sharing system and method that allows a document originator control over an electronic document shared by the document originator with at least one recipient. An input device receives an original electronic document and document-specific controls instructions pertaining to said original electronic document. By transformation, a new encrypted transformation document is created from an original electronic document, the encrypted transformation document having a transaction ID and controls instructions embedded. A recipient, if authorized, may view the encrypted transformation document after decryption within the limits set by the controls instructions such as time span over which the document may be viewed or the number of times it may be viewed.

A system may determine environmental, social, and governance (ESG) goal data for an ESG clause type and determine that a first clause of a first electronic document of a plurality of electronic documents and that a second clause of a second electronic document of the plurality of electronic documents correspond to the ESG clause type. The system may determine first ESG commitment data based on content of the first clause of the first electronic document and determine second ESG commitment data based on content of the second clause of the second electronic document. The system may generate ESG metric data based on the first ESG commitment data and the second ESG commitment data and generate dashboard data based on the ESG metric data. The system may output the dashboard data.

Document parsers, document parsing methods, and products are provided that use Visual Large Language models and / or eForms to generate structural representations to train artificial intelligence used in intelligent document processing. These structural representations are enhanced with the Visual Large Language models with geometry data from the documents and the results are correlated with a training sample. The data set is then curated for errors and omissions and reintegrated into the initial structure of the form. Auto-generated synthetic documents can be used in certain embodiments. Standardized outputs such as eForms and from an Electronic Document Interchange can be used in certain embodiments to enhance efficiency and synchronization of intelligent document processing. A multi-modal transformer-based machine learning model is built that can then be used to create an output in intelligent document processing.

The invention relates to the technical field of electronic document content review methods, particularly discloses an electronic document content review method, and aims to solve the problems that traditional manual review is low in efficiency and inconsistent in standard and implicit compliance risks are difficult to recognize. The method comprises the following steps of: performing unified analysis and OCR (Optical Character Recognition) conversion on a PDF, DOCX or TXT format document, extracting a full-amount text, and structurally dividing the full-amount text into semantic units such as a title, a term and an attachment; in combination with large-model deep semantic analysis and double-layer regular rule matching, hidden risks such as logic conflicts and fuzzy expressions and dominant violations such as terms, units and sensitive words are recognized respectively; multi-source detection results are fused, after deduplication, sorting is carried out according to risk levels, and a structured report containing problem positioning, basis and suggestion is generated; according to the method, high-precision, high-efficiency and interpretable automatic review is realized through a'large model + rule 'dual mechanism, and compliance consistency and processing efficiency are remarkably improved.

A system and method for secure and efficient automated workflows includes two complementary components. A digest embedding system verifies the integrity of workflow event sequences using a rolling SHA-256 digest salted with microsecond-precision timestamps. A template-caching extractor adaptively processes heterogeneous electronic documents. The digest system enables decentralized verification without querying centralized audit logs. The extractor uses a layout hash derived from document structure to route documents through either a low-latency, rule-based extraction path or a fallback artificial intelligence model path. New templates are generated for previously unseen layouts exceeding a confidence threshold. The disclosed methods improve latency, resource utilization, energy utilization and scalability in sectors including finance, healthcare, and logistics, offering advantages over existing prior art in terms of integration, specific mechanisms for timestamp salting, hardware security module utilization for workflow events, layout-based template caching, and adaptive learning.

The invention relates to the technical field of file automatic processing, in particular to a file identification processing system based on an artificial intelligence model and RAG, comprising the following modules: a file image preprocessing module used for receiving fax documents, scanning documents or electronic documents, and converting input documents into standardized images through denoising, angle correction and binarization processing; the file classification module is used for carrying out feature extraction on the standardized image based on a convolutional neural network and automatically classifying the file into a table type or an article type; and the article class preprocessing module is used for performing graying, binaryzation and text line segmentation on the document images classified into article classes. According to the method, through a multi-layer AI architecture of the convolutional neural network, the Transform OCR and the large language model, and in combination with a retrieval enhancement generation technology, full-process intelligent processing of documents from receiving, preprocessing, classification, OCR recognition, key information extraction to automatic routing is realized.

The invention relates to a digital and physical mixed signature method and device, electronic equipment and a storage medium, and relates to the technical field of information security, and the method comprises the following steps: calculating a document content hash value of an electronic document; obtaining random fiber distribution characteristics of a paper document bearing the electronic document, and generating a paper fingerprint hash value according to the random fiber distribution characteristics; performing data combination on the document content hash value and the paper fingerprint hash value, and performing digital signature processing on the combined hash value data by using a signature private key to generate a composite digital signature; and associating the composite digital signature with the electronic document, and outputting the electronic document for printing, so that the printed paper document is the unique physical entity bound with the composite digital signature. Through the application, an ideal balance can be obtained in three key dimensions of low cost, high safety and convenient verification, and an anti-counterfeiting means which can bind specific paper and can independently and conveniently verify is provided for a common printed piece.

A system and method for providing a virtual customer service representative (CSR) for interacting with a customer in need of a print job. Text is extracted from an electronic document defining content of the print job, and based at least in part thereon, the VirtualCSR engages in an interactive dialog with the customer regarding characteristics of the print job. A job editing interaction displays images and receives feedback from the customer to define a final appearance of the print job. Data is passed to a module that generates a plurality of print job scenarios, and a subset of scenarios above a certain prioritization focus ranking threshold is presented to the customer, from which the customer selects a final print job scenario that is the basis for the print job commissioned by the VirtualCSR in connection with the document.

The invention provides a multi-modal fusion analysis-based bid and string bid duplicate checking detection method and system, relates to the field of data processing, and solves the technical problems that in the prior art, the detection dimension of bid and string bid behaviors is single, the analysis is shallow, and all technical means cannot effectively cooperate with one another. The method comprises the following steps: acquiring bidding document electronic documents of a plurality of bidding parties, and respectively extracting text data, image data and quotation list data; processing the text data, the image data and the quotation list data, generating a corresponding text feature vector, an image comprehensive feature vector and a quotation feature vector, and obtaining a multi-modal feature vector; constructing an incidence relation graph based on the multi-modal feature vector; inputting the association relationship graph into a pre-trained graph neural network model, learning an association mode between nodes through the graph neural network model, and identifying a high-risk bidder group; the high risk represents that there are predefined similar or cooperative cheating behaviors.

The invention discloses a document layout analysis and reconstruction method based on vector topology and conflict arbitration, and relates to the technical field of document image processing, in particular to a method for carrying out accurate identification, classification and structured reconstruction on layout elements of an unstructured electronic document containing a complex vector chart. Constructing a page vector topological graph by using the bottom vector instruction and the connected topological structure; on the basis, multi-dimensional geometric features, statistical features and text mode features are introduced to jointly participate in conflict arbitration between the table and the complex graph; and applying a forced spatial exclusive constraint to text extraction by utilizing an arbitration result, and carrying out semantic classification and rearrangement in combination with a style reference and a spatial proximity relationship. According to the document layout analysis and reconstruction method, the distinguishing capacity of a table and a complex graph is improved, the attribution judgment precision of characters and a main body text in the graph is improved, and self-adaptive recognition of a title and a main body style is achieved under different layout styles.