87 results about "Document format" patented technology

The invention relates to document verification, in particular to a heterogeneous document set-oriented cross-modal semantic alignment and logic consistency verification system, which is used for heterogeneous document input, supports multi-format document input and comprises multi-modal elements including texts, pictures, tables and charts. The document analysis module is used for carrying out structured extraction on document contents; extracting multi-modal elements, identifying and classifying various elements in the document, and establishing position and type labels of a foundation; the knowledge graph construction module is used for uniformly modeling heterogeneous elements into a multi-modal knowledge graph; the graph neural network semantic alignment module is used for realizing accurate cross-modal semantic alignment by using a specially designed graph neural network based on the multi-modal knowledge graph; the hybrid consistency verification engine is used for performing logic consistency verification in combination with a symbol logic verification mechanism and a semantic consistency verification mechanism; according to the method, the defect that accurate cross-modal semantic alignment and logic consistency verification are difficult to carry out on professional documents with multi-modal elements can be effectively overcome.

The invention relates to the field of document processing, and particularly provides a document format processing method, system, terminal and medium based on a large language model.The method comprises the steps that a generation instruction containing a target document type and a source material are received, and original text content is generated through the large language model integrating domain knowledge; obtaining a matched structured format template, and analyzing the style rule into a format instruction set; identifying logic elements and hierarchical relationships thereof in the original text based on a natural language processing technology; performing association mapping on the format instruction and the logic element, and performing automatic style rendering by calling a document object model interface to generate an intermediate document with a standard format; and finally, outputting after quality verification. According to the method, an automatic process of content generation and intelligent formatting is constructed, and the document writing efficiency and normalization are improved.

A neural-symbolic hybrid system for generating binary document formats directly from natural language input comprises a binary-aware hierarchical tokenizer operating across four levels (binary bytes, structural elements, semantic content, and concepts), a constraint satisfaction engine with 64 parallel processing cores for enforcing structural integrity and mathematical consistency, format-specific processors for Excel, PowerPoint, PDF, and CAD documents, and a formal verification system generating mathematical proofs of correctness. The system includes custom AI Document Generation Processor (AIDGP) silicon spanning 600 mm2 with specialized cores providing 500 TOPS processing power. Performance characteristics include 99.7% structural accuracy, 100% format compliance, 15.3 second average generation time for complex documents, and distributed capacity of 1,000,000 documents per hour. The system eliminates intermediate conversion steps while maintaining semantic preservation through hardware-accelerated constraint satisfaction and formal verification engines ensuring structural integrity, format compliance, and security through AES-256 encryption and automated regulatory compliance across 25+ international standards.

The invention discloses a four-layer progressive mind map generation system which comprises an input module which can receive input of various document formats, supports simultaneous receiving of multiple documents and adopts a multi-source heterogeneous data adapter to unify the formats; the hierarchical preprocessing module is connected with the input module, receives the converted DOCX document data, and performs hierarchical feature enhancement and hierarchical rule configuration on the data; the bimodal processing module fuses a hierarchical driving structured extraction mode and a large language model generation mode, the hierarchical driving structured extraction mode constructs a hierarchical incidence matrix and the like, and the large language model generation mode provides task instructions and the like; and the structured output module is used for providing multi-format conversion, mind map downloading and interaction functional components. The system has the advantages that all the modules work cooperatively, multi-format document processing is achieved, multiple modes are fused to generate the mind map, rich output functions are provided, and a user can conveniently and efficiently generate and use the mind map.

The invention discloses an RAG question and answer optimization method and system based on fusion retrieval, and relates to the technical field of large model knowledge question and answer. The method comprises the steps of obtaining user query, executing keyword retrieval and semantic vector retrieval in parallel, and obtaining a keyword retrieval result list and a semantic vector retrieval result list respectively; and calculating the quality score of each text unit in each retrieval result list based on multi-dimensional quality evaluation, and filtering out the text units with the quality scores lower than a preset quality threshold value. And sorting the text units in all the filtered retrieval result lists by adopting a quality weighted reciprocal sorting fusion algorithm. And based on the length of each text unit and the document format to which the text unit belongs, performing context content enhancement and combination on each text unit after sorting, and generating an enhanced context block list. And constructing structured prompt information based on the enhanced context block list and user query, inputting structured prompt words into the large language model, and generating and outputting a final answer.

Embodiments of the invention provide a verification environment generation method and apparatus, and an electronic device. The method comprises the steps that according to a document format of a design document corresponding to a chip to be tested, the design document is recognized, and a recognition document is obtained; the recognition document is analyzed, multiple pieces of register information corresponding to the multiple registers are obtained, and the register information comprises register identifiers, boundary information and field line indexes; based on the design document, standardizing the register information corresponding to each register to generate a standardized data structure, the standardized data structure comprising a plurality of sub-data structures corresponding to the plurality of registers; based on the standardized data structure, generating a verification code meeting a verification environment specification; and integrating the verification code into the target verification environment to complete a verification task of the to-be-tested chip. The method is used for achieving the effect of improving the chip verification efficiency.

The invention belongs to the technical field of artificial intelligence and multi-modal data processing, and provides a multi-modal-based document analysis method and system. The method comprises the following steps: S1, inputting a to-be-analyzed document, and converting all pages in the to-be-analyzed document into pictures with the same size as an original page page by page; s2, performing layout analysis on the converted picture page by page by utilizing a visual model, detecting layout elements existing in the picture, and obtaining a position coordinate of each layout element; s3, inputting the current picture and the detected layout elements into a large language model for analysis, and adopting different analysis methods for different layout elements to obtain analyzed contents; and S4, displaying the analyzed content according to needs, or performing layout recovery by using the obtained position coordinates of the layout elements and the analyzed content. According to the method, the input document supports all document formats which are almost visible at present, and the analysis speed can be increased.

The invention discloses a medical examination report processing method and device, electronic equipment and a storage medium, and the method comprises the steps: processing a medical examination report, and determining report text data corresponding to the medical examination report; processing the report text data based on a big language model, and obtaining structured data which is output by the big language model and corresponds to the medical examination report; and converting the structured data into standardized data based on a standard document format, and mapping the standardized data to a medical coding system. Based on the technical scheme, a prompt project and context reasoning mechanism is utilized to guide a large language model to automatically identify the medical entity and output the structured representation, and the structured data is mapped to a medical coding system, so that seamless joint with various medical information is realized; and the real-time adaptive analysis and structuring requirements of the multi-source medical examination report can be met.

The embodiment of the invention discloses a logistics scale bill automatic operation method and system based on OCR and a large model, and the method comprises the steps: receiving a logistics scale bill image uploaded by a user, extracting initial text information through an OCR recognition module, and introducing a large model analysis module to carry out the deep semantic understanding and intelligent correction of a text, thereby achieving the automatic operation of the logistics scale bill. And meanwhile, context auxiliary verification is carried out in combination with a local knowledge base in which scale document formats and industry terms are stored, and finally, all processes are coordinated through an Agent controller and standardized data are output. According to the invention, handwritten, stained or non-standard pound sheets can be efficiently processed, full-automatic high-accuracy identification and processing of pound sheet information from images to structured data are realized, a manual input link is obviously reduced, and the efficiency of logistics operation and the data accuracy are greatly improved.

The embodiment of the invention discloses a large-model-based government affair official document intelligent generation method and device and a medium, and relates to the technical field of large models, and the method comprises the following steps: receiving an official document generation request input by a user, carrying out semantic analysis on the official document generation request, complementing missing information by querying a knowledge base and historical data, constructing a context framework, and generating a government affair official document; the official document generation request comprises an official document type, key information and a document issuing department, and the context framework comprises an official document structure template and filled entity content; generating manuscript content based on a context framework through a large language model, determining a plurality of candidate manuscript versions, and performing multi-dimensional scoring on each candidate manuscript version to determine a target manuscript version; and retrieving an official document format template corresponding to the official document generation request from a preset template library to perform semantic alignment and intelligent auditing on the target manuscript version and the official document format template so as to determine a target official document.

A digital technology transfer system transforms technology transfer documents to a set of digitized manufacturing procedures and operations documentation. The system can transform a technology transfer document to a hierarchical structured model representing a package, or product to be manufactured, and the process for manufacturing the product. The resulting package model can be integrated into a larger model representing an ecosystem of manufacturing entities and plant facilities by assigning steps of the manufacturing process to one or more selected production lines. To reduce dependency on custom-built parsers for each type of document format, the system integrating both custom and general parsing mechanisms into a scalable parser orchestration engine.

A digital technology transfer system transforms technology transfer documents to a set of digitized manufacturing procedures and operations documentation. The system can leverage generative artificial intelligence (AI) and associated trained custom models to transform a technology transfer document to a hierarchical structured model representing a package, or product to be manufactured, and the process for manufacturing the product. The resulting package model can be integrated into a larger model representing an ecosystem of manufacturing entities and plant facilities by assigning steps of the manufacturing process to one or more selected production lines. To reduce dependency on custom-built parsers for each type of document format, the system leverages generative artificial intelligence (AI) and associated trained models to extract and organize document content, and to map the document content to appropriate target data structures that can be consumed by control systems and devices.

This invention discloses a multimodal document parsing and evaluation method and system for bidding and tendering audit scenarios. First, it collects the tender documents and bid documents to be audited to obtain a set of documents to be audited. Then, it identifies the document format attributes in the set of documents to be audited to obtain initial heterogeneous corpus. Next, it performs page-level multimodal detection on the initial heterogeneous corpus and obtains detection tags. This invention achieves the function of accurately constructing audit corpus from massive heterogeneous documents using a vision-enhanced hybrid parsing strategy, and then performing multimodal document parsing and evaluation using image processing algorithms. Furthermore, the dual-modal risk assessment model combining hard and soft rules not only solves the problems of low efficiency, incomplete coverage, and easy omission of hidden risks in existing manual review, but also solves the parsing difficulties caused by poor scanned document quality. This not only makes audit compliance review more intelligent and accurate, but also significantly improves the quality and efficiency of the review.

The embodiment of the invention provides a document processing method and device.The method comprises the steps that a first document is obtained, first element content is determined from the first document, and the first element content is in a first document format; converting the first element content according to the first preset format specification information to obtain second element content, wherein the second element content is in a second document format adaptive to the preset model; and processing the second element content based on a preset model and the first preset format specification information to obtain a target processing result. According to the scheme, standardized format conversion can be carried out on the document content, the format specification information is provided for the preset model, the compatibility of data interaction between the document and the model is improved, the accuracy of a processing result is ensured, and the user experience is improved.

The application discloses a kind of file adaptive analysis method and system of battery test data, it is related to data processing technical field, the method includes: extracting the discriminative feature of to-be-analyzed file, discriminative feature is used for file format identification based on deep learning algorithm;To-be-analyzed file is parsed into structured table data based on file format information;Column type prediction information is obtained by carrying out column type prediction to structured table data based on multi-label classification model;Semantic mapping is carried out based on column type prediction information to convert to-be-analyzed file into standard format file;Feedback data of user to standard format file is obtained, and file format information, column type prediction information and semantic mapping relationship are revised based on feedback data, and closed-loop learning of deep learning model is carried out based on revision result.The application can be adapted to different file formats, no longer needs to design rule and maintain extraction template separately for each document format, and development cost is reduced.

This invention relates to the field of data processing technology, specifically to an intelligent proofreading system and method for electronic document formats based on multi-dimensional verification rules. It includes: a document structure parsing unit; a dynamic verification rule generation unit; an intelligent verification execution unit; and a verification result output unit. This invention eliminates differences in electronic document parsing. After extracting semantic blocks such as titles and body text by a paragraph-level semantic block recognition module, the intelligent verification execution unit calls a multi-dimensional rule set to verify core format elements. The verification result output unit accurately locates the page numbers, paragraphs, and character positions of deviations, generating correction guidelines and multi-format reports containing problem descriptions and compliance examples. This invention solves the problem of the lack of a formal, dedicated proofreading system for core document formats in existing technologies. It can comprehensively identify deviations and clarify the direction of correction, ensuring compliant document circulation while reducing labor costs and improving proofreading efficiency and convenience.

A computer-implemented method, a computer system and a computer program product customize delivery of transactional documents. The method includes receiving a transactional document associated with a user. The method also includes obtaining a preferred document format for the user and a preferred delivery method for the user from a database. The method further includes identifying a current display format of the transactional document. In addition, the method includes modifying the current display format of the transactional document, wherein a modified transactional document has the preferred document format for the user. Lastly, the method includes transmitting the modified transactional document to the user using the preferred delivery method for the user.

The invention discloses a method for improving stability and question and answer accuracy of large language model driving software, which comprises the following steps: step A, input preprocessing: carrying out double-path preprocessing on files and questions, detecting abnormal files through format compatibility and instruction injection, and constraining an answer range; b, dynamically processing routing: dynamically routing according to a document format and a problem intention, and performing content conversion and solution by adopting multiple strategies including code generation; and step C, result verification and self-correction: through a retry and logic consistency check mechanism, verification and self-correction are carried out on an output result to ensure that a conclusion is reliable. According to the method, non-intrusive deployment is adopted, the universality, stability and question and answer accuracy of software are improved, the engineering integration cost is reduced, a table file answer error classification method is further provided, and guidance is provided for tool optimization.

The application relates to the field of artificial intelligence and natural language processing technology, and proposes a self-adaptive document generation method and system based on a knowledge graph and a large model.The application is based on a document generation request input by a user;extracts entities from multiple source data and constructs and updates a queryable knowledge graph;combines a user request, a current generation context and feedback of the knowledge graph to dynamically plan the structure, detail level and expression style of a document;based on a planning result, searches for related knowledge segments from the knowledge graph as conditions to drive a pre-trained large language model to generate coherent text content;structurally organizes the generated text content according to semantic roles, and renders the text content into a readable document format based on a dynamic template to output.The application realizes the organic combination of knowledge driving and language generation, can flexibly cope with document generation tasks in different scenarios through an adaptive mechanism, and improves the efficiency and effect of information transmission.

The invention provides an intelligent bidding document compiling method and device based on a Word-like editing technology, and relates to the technical field of artificial intelligence. According to the method, the target intelligent content block, the target data field and the modification content in the editing operation of the user are analyzed, so that the change intention is accurately identified, and errors or omission caused by manual blind modification is avoided; then, the bidding file is automatically traversed based on the target data field, all to-be-updated intelligent content blocks and positions are rapidly positioned, synchronous updating of multi-position data is achieved, the tedious process of manual one-by-one searching and modification is eliminated, and the repeated labor time is shortened; finally, the document format is intelligently maintained in the updating process, and the problem of format disorder caused by manual adjustment is prevented. According to the method and the device, the technical problem of low efficiency caused by tedious modification and disordered formats in the bidding document compiling process is solved, the compiling period is shortened, meanwhile, the risk caused by human factors is reduced, and the compiling efficiency of the bidding document is improved.

The present invention relates to a secure artificial intelligence based document management and intelligent content classification system implemented within a controlled enterprise computing environment for regulated industries. The system is configured to receive digital documents from multiple enterprise sources, normalize heterogeneous document formats into a standardized internal representation, and perform multi-dimensional content analysis to extract structural, semantic, and metadata characteristics. Adaptive artificial intelligence based classification logic is applied to determine document category, sensitivity, and regulatory relevance, followed by computational validation procedures that ensure deterministic and auditable classification outcomes. The invention further incorporates document content fingerprinting, continuous integrity monitoring, and real-time regulatory compliance evaluation to prevent unauthorized modification, misclassification, or non-compliant document handling.

The invention discloses a multi-source software engineering document analysis and evaluation report generation method and system based on generative AI, and the method comprises the steps: constructing a cross-document relation graph, and storing the cross-document relation graph in a knowledge base; establishing a dynamic evaluation rule engine, presetting a document format standard template in the industry, setting evaluation dimensions, and establishing a rule executor by setting a rule for judging whether a test is completed or not according to requirements; an AI report generation module is generated in a constraint form, and a traceability mark is embedded; a final evaluation report is generated by manually checking an AI report and a knowledge base evidence chain; the system comprises a multi-source document processing module, a joint information extraction and knowledge graph construction module, a dynamic evaluation rule engine module, a constrained generative AI report generation module and a man-machine collaborative auditing feedback module. According to the method, the problems of accuracy, compliance and traceability in automatic generation of the system evaluation report are solved, and efficient, standard and audible software evaluation report output is realized.

The invention relates to the technical field of computers, and provides an interface registration method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining a to-be-registered interface document submitted by an interface provider; preprocessing the to-be-registered interface document to obtain target document information; wherein the target document information at least comprises target interface information; performing information extraction on the target document information through a pre-trained information extraction model to obtain normalized interface description information; and generating routing configuration information of an application programming interface (API) gateway based on the normalized interface description information, and registering the routing configuration information to the API gateway. The application can adapt to and efficiently process different interface document formats, and automatically register to the API gateway according to the standardized interface description information obtained by processing, and manual intervention is not needed in the whole process, so that the labor cost and the time cost can be greatly saved.

The invention discloses a word processing method and device. The method comprises the following steps: reconstructing a document structure into one or more article units; in response to the triggered target article unit, displaying an editing page of the target article unit; in response to a triggered typesetting editing operation of the editing page, performing typesetting editing on the target article unit by using a WYSIWYG editing mode and a LaTeX fragment to generate fusion content; the fusion content is rendered in a compiling rendering mode, a rendering result is obtained, and a final document is generated. By splitting the document into the plurality of article units and combining with the LaTeX fragments to realize typesetting editing, the limitation of an existing WYSIWYG character processor in processing complex typesetting requirements is solved, the typesetting effect of a single LaTeX fragment or the whole unit can be previewed in real time when the article units are written, and adjustment is carried out according to the typesetting effect, so that the typesetting efficiency is improved, and the typesetting efficiency is improved. Therefore, the consistency and high-quality output of the final document format are ensured, and professional typesetting requirements are met.

The invention discloses a file adaptive analysis method and system for battery test data, and relates to the technical field of data processing.The method comprises the steps that discriminative features of a to-be-analyzed file are extracted, and the discriminative features are used for file format recognition based on a deep learning algorithm; analyzing the to-be-analyzed file into structured table data based on the file format information; performing column type prediction on the structured table data based on a multi-label classification model to obtain column type prediction information; performing semantic mapping based on the column type prediction information to convert the to-be-analyzed file into a standard format file; and obtaining feedback data of a user on the standard format file, correcting the file format information, the column type prediction information and the semantic mapping relationship based on the feedback data, and performing closed-loop learning of the deep learning model based on a correction result. The method can adapt to different file formats, rules do not need to be independently designed and extraction templates do not need to be maintained for each file format, and the development cost is reduced.

The invention discloses a Word document format conversion method capable of configuring rules and cooperating with a natural language, which comprises the following steps of: S1, configuring a document format, and obtaining a structured parameter of a target format; s2, carrying out Word document analysis and structured conversion; s3, reconstructing a depth style of the HTML document; and S4, converting the processed HTML document into a docx format file, performing format conversion on the LaTeX code in the document, converting the LaTeX code into an Office mathematical formula object, and finally outputting a standardized Word document. The original Word documents in various formats can be processed, the standard Word documents output after processing do not have the situation of format disorder or content loss, and the problems that in traditional document format conversion, operation is complex, formats are not uniform, and formulas cannot be edited are effectively solved.

The invention provides a document structured conversion method based on layout detection and a rule engine, which belongs to the technical field of artificial intelligence and document information processing, and comprises the following steps: receiving and initializing a document task, identifying structural elements by a layout model, correcting a structure and reconstructing a multi-level title, associating and restoring an image and a table structure, and generating and storing a preset document. And a task process state tracking and control mechanism. The problems of unclear structure, disordered format and the like of the traditional OCR are solved, and the method adapts to various complex document formats; subsequent content reutilization, intelligent question answering and knowledge extraction are facilitated; the system stability and the engineering deployment capability are improved; and the method adapts to different use scenes and demand changes.

The invention belongs to the field of document tool integration, and relates to a demand document labeling and structured analysis method and system and a storage medium, and the method comprises the following steps: S1, defining labels, and carrying out classified labeling on titles and tables to form a label set; s2, performing deep analysis on the document structure by using an analyzer of the label set; s3, data cleaning is carried out, the document format is automatically adjusted to adapt to the requirement of a target system, and seamless importing of the document is achieved; according to the method, the demand document is seamlessly imported into the target system based on label analysis, the importing efficiency can be improved, the data accuracy is ensured, the complexity of user operation is greatly reduced, document importing becomes easy and efficient, and the problem that in the demand document importing process, the user experience is poor is solved. Users often face the problems of tedious operation, low import efficiency, disordered formats and the like.

The application discloses a document format conversion method and device, a storage medium and equipment. The method comprises the following steps: identifying a table in a PDF document, wherein the table comprises at least one of a full-frame table, a half-frame table and a frameless table; identifying a chart in the PDF document, wherein the chart comprises at least content information displayed in a graphic manner; and converting the PDF document into an HTML document according to the table and the chart, wherein the converted table in the HTML document is in an HTML form, and the converted chart in the HTML document is in a picture form. The embodiments of the application can effectively identify various elements such as the full-frame table, the half-frame table, the frameless table and the chart in the PDF document, and convert the various elements into the HTML document, thereby improving the accuracy of the PDF document format conversion.