132 results about "Document format" patented technology

The embodiment of the invention provides a method and system for automatically generating a document based on a template and a large model, and relates to the technical field of document generation, the method comprises the following steps: step S1, a user inputs information through a browser interface and uploads a to-be-reviewed file; step S2, analyzing the uploaded multi-modal file and extracting structured data; s3, outputting a standardized template instance file according to the decision tree dynamic combination template; s4, calling a large model to generate a project background and a file content abstract; s5, the generated content is rendered and combined with the attachment to form a complete conference review file; s6, executing cross-document consistency intelligent verification and executing intelligent error correction; and S7, generating and storing a final document with version traceability information. According to the method, on the basis of the document template and the large model capacity, document formats are unified, content is accurately generated, and the document writing efficiency is remarkably improved.

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.

The invention discloses a system and a method for enhancing generation of hydrofracture questions and answers based on cross-language retrieval. The knowledge question-answering system aiming at the hydraulic fracturing field is developed by utilizing a cross-language retrieval enhancement generation technology, so that a user can obtain an optimal answer and a corresponding source from a multi-language knowledge base by matching only by using Chinese retrieval; the complex process that a user needs to find useful information from numerous and jumbled papers and reports is changed. According to the system, a dynamic text vector library framework is adopted, multi-language and complex document formats are supported, the analysis function of tables and formulas is integrated, documents in the hydraulic fracturing field are stored in the same knowledge base, the knowledge base is continuously updated along with document expansion in the professional field, a user can inquire related problems in the field in the system, and the user experience is improved. By integrating and updating a large amount of document information, required professional knowledge in the field can be efficiently obtained.

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 provides an official document generation method and system fusing document analysis and cognitive reasoning, and the method comprises the steps: carrying out the multi-modal feature extraction of an input original document through employing an analysis engine combining a convolutional neural network and a graph attention network, and obtaining the multi-modal data in the original document; based on the multi-modal data, generating a classification decision result of the multi-modal data by using a hierarchical classifier enhanced by a knowledge graph; based on the multi-modal data and the classification decision result, generating a task decomposition result by combining a cognitive inference engine; and based on the classification decision result and the task decomposition result of the multi-modal data, generating an official document by combining compliance constraint with an official document format template, so that multi-modal accurate analysis of a complex document can be realized, and dynamic semantic understanding and classification are realized by utilizing a hierarchical classifier enhanced by a knowledge graph. The classification accuracy in the fuzzy semantic scene can be improved, so that the recognition error rate can be reduced, and the accuracy can be improved.

The invention discloses a communication protocol automatic analysis and test data generation method and system, and the method comprises the steps: analyzing an unstructured protocol document, recognizing a fixed field and a variable field in the document, and outputting structured data; automatically generating test data based on the structured data, dynamically calculating a checksum according to a specified check algorithm type in the structured data, and filling the checksum into the original message to form a complete test message; and generating a standardized test data set according to the complete test message. According to the method, manual intervention is not needed from document analysis to test data generation, the analysis efficiency is improved, and most protocol scenes are covered through the boundary value, the abnormal value and the orthogonal combination strategy. The method supports various document formats, data types and verification algorithms, adapts to protocol standards of different industries, facilitates problem positioning and regression testing through standardized output documents, and reduces the maintenance cost.

The invention particularly relates to a Word document format conversion method based on Java. The Word document format conversion method based on Java comprises the following steps: analyzing the content of an original. Doc file, and extracting text paragraphs, tables, pictures, style information and document metadata; the extracted content is divided into different categories, and the XML node type corresponding to each category of elements in the target. Docx document is established; the method comprises the following steps of: constructing a pattern mapping rule base, constructing a new. Docx document structure by using an XWPF Document object model according to an Office Open XML (Extensible Markup Language) specification, sequentially inserting paragraphs, tables and pictures, and applying corresponding pattern configuration; and outputting and generating a. Docx file, detecting and processing abnormal conditions, and recording a conversion log at the same time. The Word document format conversion method based on Java is efficient and accurate, has good compatibility, expandability and cross-platform capability, is suitable for enterprise-level document management systems, cloud services and batch document processing scenes, and remarkably improves document compatibility and processing efficiency of office automation systems.

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.

The invention relates to a railway official document keyword extraction method and device and electronic equipment, and the method comprises the steps: based on a pre-constructed railway official document format rule base, extracting a key field of a fixed position from an input text through regular expression matching and position locking; a Jieba word segmentation device is used for loading a railway-specific term library for word segmentation, and a multi-word combination entity boundary is dynamically corrected through a dependency relationship rule; executing a TF-IDF algorithm on the text after word segmentation to generate an initial word weight, adjusting the weight according to the position area of the word in the official document and a preset coefficient, and performing position weighting; and combining the words of which the weights are greater than a set threshold value with the extracted key fields, and outputting a final keyword set after verification of a term library. According to the method, missing detection caused by low frequency of a traditional algorithm is avoided, splitting errors of a general word segmentation device are eliminated, the term recognition error rate is reduced, the core word sorting priority is improved, and the semantic weight of keywords is strengthened; the new term storage time is shortened, and the updating cost problem is solved.

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 discloses an intelligent document writing system based on a large language model, belongs to the technical field of natural language processing and intelligent office crossing, and aims to solve the technical problems of how to realize intellectualization, standardization and high efficiency of a whole document writing process and improve document writing efficiency and accuracy. According to the technical scheme, the system comprises an input layer, a core layer and an output layer; the input layer comprises a multi-modal input interface and a demand analysis engine; the multi-mode input interface is used for voice input and text input; the demand analysis engine is used for text recognition and automatic element providing, and only subject fields can be filled and document unit fields can be received; the core layer is used for adopting a mixed training strategy of comparative learning and curriculum learning, improving professional field content generation capability, integrating format verification and an OCR feedback mechanism, ensuring document format compliance and supporting a quick response mechanism of standard updating; and the output layer is used for realizing export and version management of documents in standard DOCX, signature PDF and HTML5 formats.

The invention discloses an official document processing method and device based on a large model and an official document generating and checking all-in-one machine. The official document processing method based on the large model can quickly respond to a user request, automatically match and call a pre-trained official document generation sub-model corresponding to a literary and sports category by automatically identifying an official document title and an official document keyword, and automatically process the official document in combination with knowledge base data of a corresponding application field. According to the method, the large language model technology is utilized to quickly and intelligently generate the official document file with high quality, official document processing which is specially refined in various official document styles and is combined with the user industry can be realized, and the official document processing efficiency is greatly improved. According to the document generating and checking all-in-one machine, software and hardware are perfectly combined, the problems of document format accurate generation, large model illusion, safety risk, computing power support and the like can be solved at the same time, safe and efficient operation of the all-in-one machine in a user intranet environment is achieved, and the difficulty and cost of building and maintaining a complex system by a unit are reduced.

The invention relates to the technical field of computers, and discloses a document format conversion method and device for large model training, and the method comprises the steps: carrying out the classification of a PDF document based on a plurality of classification indexes, and obtaining a document type; when the document type is an image type, performing image conversion and preprocessing to obtain a preprocessed page image; analyzing the preprocessed page image to obtain multi-modal content, and processing the multi-modal content to obtain corresponding processing results; performing content reconstruction and optimization on the PDF document to obtain a first intermediate document; and performing content rearrangement on the first intermediate document to obtain a Markdown document. According to the method, the PDF documents are accurately classified by integrating multiple dimensions, different types of documents are subjected to differentiated format conversion, the format conversion efficiency and accuracy are improved, the generated Markdown document conforms to the original PDF document, semantic coherence and format standardization are achieved, the large model input requirement is met, and therefore the model training effect can be improved.

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 invention provides a medical document multi-language intelligent analysis system, relates to the field of language translation, and improves the accuracy and efficiency of professional term translation. The method comprises the following steps of: firstly, performing language recognition on an original text document by a recognition module through text unitization and context vector generation, and matching a corresponding corpus; then, a translation module carries out lexical element alignment on the source lexical elements through term bank injection and an AI model, the translation process is automatically optimized, and accurate translation of the terminologies is ensured; and finally, the reconstruction module accurately replaces corresponding contents in the original text document with translation output through the mapping file, so as to ensure that the document format and typesetting are consistent. Through the automatic and optimized translation process, the quality and efficiency of professional term translation are remarkably improved, manual intervention is reduced, and the translation requirement of a high professional standard is met.

The invention discloses an LLM-based medical translation model training method and a medical document translation method. The model training method comprises the steps of constructing a Chinese-English medical corpus, pre-training a medical translation model, finely tuning the medical translation model, quantifying the medical translation model and deploying the medical translation model. The medical document translation method comprises the steps of document format conversion, document preprocessing, medical document translation, document post-processing and document format restoration. According to the medical translation model training method and the medical document translation method based on the LLM, the accuracy of medical translation is remarkably improved, professional terms, complex sentence patterns and context logic relations in medical texts are efficiently understood and translated, and translated texts which are more natural, smoother and higher in accuracy can be generated.

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 invention relates to the technical field of document and image processing, and provides a format conversion method and system based on multi-modal fusion and generative adversarial networks, and the method comprises the steps: obtaining document layout information of a document format original file through a deep learning model according to the extracted document multi-modal information of the original file, obtaining document conversion style information by utilizing a document generative adversarial network model according to the document layout information and the first target style requirement, and converting the original file into a PDF format file according to the document conversion style information; for the image format original file, obtaining image understanding information by using an image analysis model according to the extracted image multi-modal information of the original file, and obtaining image conversion style information by using an image generative adversarial network model according to the image understanding information, a target image type requirement and a second target format requirement, and converting the original file into a PDF format file according to the image conversion style information. And PDF files meeting specific requirements are efficiently and accurately formed.

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 present invention belongs to the field of document recognition and provides a document recognition method, system, and device based on a large model. The method acquires document image data containing text information and preprocesses the acquired document image data. The preprocessed image is evaluated for image quality, language distribution, and layout complexity. The evaluation results are integrated to determine the processing path for the document image data. Based on the determined processing path, the corresponding optical character recognition model is called to extract the text information from the document image data. The extracted text data is subjected to in-depth semantic analysis using a pre-trained deep learning large model to extract key feature information. The text information or the extracted key feature information is subjected to rule compliance analysis, and a recognition analysis report is generated based on the analysis results. The present invention improves processing speed and accuracy, enhances adaptability to various document formats, and effectively addresses the limitations of the existing technology.

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.