1109 results about "Digital document" patented technology

The invention provides a talent evaluation management method and system based on AI intelligence, and relates to the technical field of artificial intelligence analysis, and the method comprises the steps: S1, converting a handwritten resume image into structured text data through OCR image recognition; converting the interview record into a dialogue text with a time sequence mark through voice transfer; performing format analysis on the electronic document to extract original text content; performing coding standardization processing on the structured text data, the dialogue text and the original text content to generate a standardized text data set containing semantic tags; and S2, performing context semantic coding on the standardized text data set, performing node alignment and semantic disambiguation processing on professional terms through a domain knowledge graph, and generating a text feature vector containing an entity association relationship. According to the method, through multi-source data integration, semantic deep analysis and dynamic matching calibration, the talent ability is accurately evaluated, the result is scientific and quantitative, and intelligent and interpretable talent evaluation and decision support is provided.

A digital content management system may include a set of one or more memory components and a set of one or more processing devices coupled to the set of one or more memory components. The set of one or more processing devices to perform operations comprising: obtaining one or more electronic signatures on a digital document to yield an electronically signed digital document, storing the electronically signed digital document at an off-chain address, using a trained machine learning model to create a smart contract, the smart contract comprising a reference to the off-chain address; and deploying the smart contract to a blockchain.

Methods and systems for a document review process are provided. The method includes receiving an input digital model representation comprising at least one externally-accessible model endpoint for generating a digital artifact. Then, generating a document splice comprising access to multiple document subunits, with at least one document subunit written in a natural language and comprising the digital artifact; the access to each document subunit is provided through an externally-accessible document endpoint for the subunit. Then, generating a document by combining the document subunits, and generating a view associated with the document, based on an user authorization result including selective access rights to the document subunits. The view comprises access to the digital model representation, the digital artifact, each document subunit, and the document. Finally, receiving a user input and updating, via one of the externally-accessible document endpoints, the document splice based on the user input.

The invention relates to the technical field of management and control systems, in particular to a digital intelligence system applied to collaborative management and control of water-power engineering construction participating units, which comprises a project data management module covering water-power engineering construction full life cycle management, extracting multi-source information data from various subsystems, and constructing a project view and a project management information base; the project risk analysis module is used for constructing an intelligent risk analysis model for risk analysis and generating a dynamic evaluation result, a graded early warning notification and an auxiliary decision scheme; the project collaborative management module is used for processing graded early warning notification and auxiliary decision-making schemes by using a multi-layer perceptron model, and generating finalizing service achievements and management process records; and the project document management module is used for performing compliance automatic checking and processing on the electronic documents needing to be archived, and dynamically updating and optimizing the project management information base. Through the closed-loop management and control system, the cooperative management and control efficiency of water-power engineering construction participation units is improved.

A method including receiving a digital image including text arranged in a layout. The method also includes generating, by an optical character recognition model, a layout text vector that encodes at least one word in the text of the digital image and a position of the at least one word in the layout of the digital image. The method also includes generating, by a visual encoder model, a visual representation vector embedding a content of the digital image. The method also includes converting both the layout text vector and the visual representation vector into a projected text vector including a digital format suitable for input to a large language model. The method also includes combining, into a prompt, the projected text vector, a system message, and a task instruction. The method also includes generating an output including a key-value pair.

The present disclosure provides a method for securing document content. A document security manager receives a digital document containing original text and image content. The original text content is processed to identify text portions by parsing annotations, analyzing proximate text, extracting content within the determined scope, and determining encryption attributes. The original image content is processed to identify image portions by detecting user-defined selections or employing a neural network to identify sensitive objects. Encrypt content requests are generated including the identified text and image portions with associated attributes and metadata. The requests are transmitted to a cryptographic engine, which returns encrypted content. A partially encrypted document is built by replacing original content with masking symbols, applying visual obfuscation, embedding encrypted content as metadata, and updating document properties to indicate encrypted content.

The invention discloses an enterprise-level knowledge management system based on a large language model. The enterprise-level knowledge management system comprises a knowledge storage module, a knowledge analysis module and a knowledge application module, the knowledge storage module is responsible for managing and storing knowledge from different sources, supporting uploading, updating, deleting and sharing of electronic documents and multimedia documents, and is provided with authority control; the knowledge analysis module is used for carrying out deep understanding and structured processing on text and multimedia contents through a special analyzer by utilizing an advanced large language model technology; the knowledge application module provides intelligent retrieval and intelligent question and answer functions and supports advanced applications such as behavior portrait analysis and standard process supervision. According to the method and the system, the acquisition, understanding and application efficiency of enterprise knowledge is remarkably improved by fusing a large language model technology and a traditional knowledge management method, an intelligent, automatic and safe knowledge management solution is provided for an enterprise, and value mining and innovative application of enterprise knowledge assets are effectively promoted.

A method for packaging digital evidence for long term validation comprises forming a package of a digital document (10), an electronic signature (12) for the document (10), together with evidence (16) of the authority of the signature in the document and a time stamp (20) indicating when the document was digitally signed. All of the pieces form parts of the packaged evidence.

The invention discloses an electronic archive data security system and method, and relates to the technical field of electronic document management. The electronic archive data preservation method comprises the following steps: acquiring a plurality of storage files to be stored and file attribute data of each storage file in real time; analyzing the risk level value of each storage file according to the file attribute data of the storage files, and marking the risk level value; classifying and storing the plurality of marked storage files into an electronic archive database; after a plurality of storage files are stored in a classified mode, time period access data of each storage file are obtained in real time, and real-time analysis is carried out in combination with risk level values. File attribute data are obtained in real time, and risk level evaluation is carried out on the file attribute data, so that the files can be marked and stored in a classified mode in real time; according to the method, the high-risk file is ensured to accept stricter protection measures, the risk assessment index is updated in real time, and the encryption strength is dynamically adjusted according to the risk assessment index, so that the protection capability on sensitive information is remarkably improved.

The invention provides a multi-feature information hidden document integrity verification and tampering positioning method, and relates to the field of network security and digital document protection. The multi-feature information hidden document integrity verification and tampering positioning method comprises the following steps: S1, document multi-dimensional feature extraction and encryption: based on an original Word document, adopting an SHA-3 algorithm to calculate a full-text hash value as a content feature, and extracting document object model features such as paragraph hierarchy, table structure and the like through a DOM tree analyzer; after the two types of features are combined into a feature matrix, a dynamic secret key is generated through Logistic chaotic mapping for XOR encryption, and an encrypted document feature matrix is generated. A dynamic key is generated by combining Logistic chaotic mapping encryption through a multi-dimensional extraction technology fusing document content hash values and structural features, so that the anti-cracking capability of a feature matrix is remarkably improved, the confidentiality of document features in open network transmission is ensured, the block information retention rate is simulated and predicted by adopting Monte Carlo, and the watermark embedding weight is dynamically allocated.

The present disclosure is directed toward systems, methods, and non-transitory computer readable media that provide a contextual query answering system that trains and implements a unique machine learning architecture to generate accurate domain-specific contextual responses. For example, the disclosed systems receive a contextual query indicating a software context of a computer application within a software-specific domain. The disclosed systems utilize a context retrieval model to generate query embeddings from the contextual query and data segment embeddings from data segments of stored digital documents. Further, the context retrieval model determines relevant digital documents from among the stored digital documents based on comparing the query embeddings and the data segment embeddings. The disclosed systems provide the relevant digital documents to a response generator model to generate a contextual response within the software-specific domain.

The invention provides a student growth archive management method, which comprises the following steps of: performing structured processing on multi-source heterogeneous data of paper archives, electronic documents and audio and video data by adopting a data acquisition and conversion technology according to heterogeneous data characteristics of student growth archive management, performing data cleaning, conversion and integration operation to obtain unified structured digital information, and storing the structured digital information into a database; a foundation is laid for subsequent big data analysis; based on a result of machine learning analysis, a student portrait and a knowledge graph are constructed, a comprehensive and dynamic student personal file is formed through multi-dimensional description of learning tracks, ability characteristics and psychological characteristics of students, entities such as students, courses, teachers and the like and relationships thereof are visualized by utilizing a knowledge graph technology, and a knowledge graph is created. The association relationship and influence factors among the students are mined, and a basis is provided for personalized education and accurate teaching.

A computer-implemented method for searching electronic documents is provided. The method executing a non-semantic search, such as lexical search, to identify documents from a document corpus that meet the search criteria of the non-semantic search. A subsequent semantic search can be scoped based on the results of the non-semantic search. The method can thus include executing a semantic search scoped to the documents identified in the non-semantic search result to generate a semantic search result that identifies content that is semantically relevant to a natural language query. Thus, the semantically relevant content can have both non-semantic (e.g., lexical) and semantic relevance.

The present disclosure provides a method for securing document content. A document security manager receives a digital document containing original text and image content. The original text content is processed to identify text portions by parsing annotations, analyzing proximate text, extracting content within the determined scope, and determining encryption attributes. The original image content is processed to identify image portions by detecting user-defined selections or employing a neural network to identify sensitive objects. Encrypt content requests are generated including the identified text and image portions with associated attributes and metadata. The requests are transmitted to a cryptographic engine, which returns encrypted content. A partially encrypted document is built by replacing original content with masking symbols, applying visual obfuscation, embedding encrypted content as metadata, and updating document properties to indicate encrypted content.

A method for AI-driven natural language search includes receiving a user query for one or more items from a user, processing the user query by searching against at least one relational database associated with the query, where the relational database is generated by extracting features from electronic documents of a plurality of items associated with the one or more items and by identifying specifications or respective values corresponding to the extracted features of the plurality of items, generating one or more query results based on the processing of the user query, where the one or more results include at least one item identified from the plurality of items and a justification for explaining an irrelevance of the at least one item, and transmitting the one or more query results to a user device for presentation to the user.

Methods and systems for artificial intelligence (AI)-based document retrieval during a virtual meeting are provided herein. Discussion data based on multi-media stream(s) provided by client devices of participants of a virtual meeting is obtained. A determination is made of whether the discussion data corresponds to an information access query. In response to a determination that the discussion data corresponds to the information access query, the discussion data is provided as input to an AI model trained to identify one or more electronic documents including content that is relevant to given discussion data. An electronic document associated with at least one of the participants including content that is relevant to the given discussion data is identified based on output(s) of the AI model. At least a portion of the content of the electronic document is provided for presentation via a user interface (UI) at each client device associated with the participants.

A method, an apparatus, and a computer-readable storage medium for generating a document graph. A plurality of electronic documents is received. Each electronic document has a predetermined document type. A machine learning model is selected from the plurality of machine learning models based on the predetermined document type. The selected machine learning model is instructed to extract a plurality of document portions from each electronic document in the plurality of electronic documents in accordance with the predetermined document type. A relationship between two or more document portions is defined based on the content of each document portion, and the document portions are associated based on the relationship. A graph structure having a plurality of nodes is generated. Each node includes at least one document portion. Each node is connected to another node in accordance with the relationship between document portions included in the nodes. The graph structure is stored.

The present disclosure relates to systems, methods, and non-transitory computer-readable media that iteratively generates, utilizing a machine learning model, text responses to reduce hallucinated content. In particular, in some embodiments, the disclosed systems receive a digital query and selects one or more supporting digital documents for the digital query. Furthermore, in some embodiments the disclosed systems generate a first text response from a first text prompt generated by using the digital query. Moreover, in some embodiments the disclosed systems extract a misalignment portion of the first text response by comparing the first text response and the one or more supporting digital documents. Additionally, from the misalignment portion of the first text response and the digital query, the disclosed systems further generate a second text response.

Presented herein are interactive graphical user interfaces (GUIs) for providing automated, real-time interactive assistance to a human user creating electronic documents. In certain embodiments, the GUI includes an alphanumeric text processing region, an AI-generated text region, and a reference list region. The AI-generated text region contains one or more alternative blocks of text responsive to a user query and based on specific references (e.g., articles, books, or other written works). The references are listed in the reference list region of the GUI.

Methods and systems for generating a live digital document are provided. The method includes receiving a static document file including human-readable data. Then, parsing the static document file into a plurality of subunits. Then, generating a sharable document splice of the static document file. Hie sharable document splice includes access to a subset of the plurality of subunits, and the access is provided through an Application Programming Interface (API) or Software Development Kit (SDK) endpoint for each subunit in the subset. Then, executing a digital thread script to generate the live digital document from the sharable document splice and an input digital model representation, using API or SDK endpoints in the sharable document splice. The live digital document is configured through the digital thread script to reflect changes in the input digital model representation. Finally, adding execution metadata for the execution of the digital thread script to the live digital document.

The invention relates to the technical field of intelligent file processing, and discloses an element extraction method and device of a test report, computer equipment and a storage medium, the method comprises the following steps: obtaining scanning document documents of a plurality of paper test reports, and screening out a multi-modal format document from the scanning document documents; identifying and extracting text features, picture features and table features in the multi-modal format document based on an optical character identification technology model; performing paragraph combination on the extracted text features; and extracting structured data from the text features, the picture features and the table features after paragraph combination by adopting a multi-modal element extraction model to obtain a complete electronic document corresponding to the multi-modal format document. Based on an optical character recognition technology, character features, image features and table features in various paper test reports are accurately recognized and extracted by using a number, image and character recognition and extraction technology, and the recognition and extraction accuracy and extraction efficiency are improved.

The invention discloses a document digital processing method and device and a nonvolatile storage medium. The method comprises the steps that a to-be-processed area is determined in a target document image, and the area type of the to-be-processed area comprises a text area and a table area; an encoder in the document digital processing model is adopted to extract area visual features of the to-be-processed area; processing the regional visual features by adopting a first decoder in a document digital processing model to obtain spatial layout information and regional content information of the to-be-processed region; processing the regional visual features by adopting a second decoder in a document digital processing model to obtain structural information of the to-be-processed region; and obtaining a digital document corresponding to the target document image according to the spatial layout information, the region content information and the structure information of each to-be-processed region. According to the method and the device, the technical problem that the document digitization effect is poor due to the fact that the table part of the document cannot be accurately recognized in the related technology is solved.

The embodiment of the invention provides a document-based intelligent question and answer method and device, electronic equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: performing document analysis on a target electronic document to obtain document attributes and document contents; based on the document attribute and the document content, document segmentation is conducted on the target electronic document, document segmentation units and unit position information of the document segmentation units are obtained, and the document segmentation units comprise segmentation unit identifiers; based on the document attribute, performing network construction on the target electronic document to obtain a document structure tree network; on the basis of the unit position information, the document segmentation units are arranged in sequence, and a document linear list is obtained; performing document query on the document structure tree network or the document linear list based on the document problem information and the segmentation unit identifier to obtain document query information; and based on the document query information, performing question reply on the document question information. According to the embodiment of the invention, the intelligent question and answer accuracy based on the document can be improved.

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.

Techniques for hybrid natural language generation (NLG) using a symbolic NLG engine and a large language model (LLM) are disclosed. The techniques include: obtaining a first text segment configuration; obtaining values of at least some of a first set of data variables; generating a first natural language text segment for an electronic document using a first text segment configuration, the values, and the symbolic NLG engine; obtaining an initial text segment; obtaining a second text segment configuration specifying information to use for generating a second natural language text segment using the ML NLG engine from the initial text segment; generating a second natural language text segment for the electronic document by using the initial text segment, the second text segment configuration, and the ML NLG engine; and outputting the generated electronic document.

The invention relates to the technical field of computers, and provides a document digitization method and device, electronic equipment and a readable storage medium. The method comprises the following steps: converting original data into a to-be-processed electronic document in a specified format; performing primary page classification processing on the to-be-processed electronic document to obtain a primary page classification result; based on the primary page classification result, determining a page information extraction strategy for the to-be-processed electronic document; extracting key information elements and a page text set from the to-be-processed electronic document based on a page information extraction strategy; and performing structured processing on the key information elements and the page text set to obtain structured data corresponding to the to-be-processed electronic document, and storing the structured data. According to the method, deep intelligent digital processing can be carried out on the original data from different data sources, the processing efficiency is high, and subsequent data processing analysis and retrieval utilization are facilitated.

Systems and methods are disclosed for training an electronic document extraction model, including the generation of the training data to train the model based on sampling a pool of electronic documents based on a rareness metric of the documents. Each electronic document has a document-level rareness metric generated, with the document-level rareness metric being based on one or more of a structural rareness metric or a content rareness metric of the document. The structural rareness metric measures the rareness of the document structure, which may be irrespective of the text content of the document. The content rareness metric measures the rareness of the document content, which may be irrespective of the document structure. The electronic documents are sampled based on the document-level rareness metrics to increase the number of rare documents in the training data without unduly biasing the sampling to optimize the training data for training the extraction model.

An apparatus comprises at least one processing device configured to receive a cryptographically attested digital document from an onboarding management system, wherein the cryptographically attested digital document comprises one or more credentials for at least one device requesting access to a secure communication channel to communicate with the onboarding management system. The at least one processing device is further configured to verify whether the cryptographically attested digital document is valid, and identify the one or more credentials in response to verifying that the cryptographically attested digital document is valid. The one or more credentials are transmitted to at least one authenticator in response to a request from the at least one authenticator to authenticate the at least one device. The at least one device is given the access to the secure communication channel responsive to verification of the one or more credentials by the at least one authenticator.

Embodiments extract a key phrase from an online profile of a user of a professional social network (PSN) and identify a set of skills associated with the key phrase. A set of skill embeddings corresponding to the identified set of skills may be retrieved from a store of skill embeddings. The skill embeddings may be pre-created by a large language model (LLM). The retrieved skill embeddings may be aggregated to create a skill-centric digital representation of the user. Based on the skill-centric digital representation of the user, a subset of digital documents may be identified to present to the user via the PSN.

A method, an apparatus, and a computer-readable storage medium for executing obligation management. One or more document portions are extracted from an electronic document using at least one machine learning model selected from a plurality of machine learning models based on at least one parameter associated with the electronic document. One or more entities are identified in one or more document portions of the electronic document. The entities are sent to a generative artificial intelligence (AI) model. The generative AI model is configured to generate one or more rules defining one or more obligations associated with one or more entities. One or more rules are executed to monitor compliance with one or more obligations by one or more entities.