50 results about "Document analysis" patented technology

This invention discloses an intelligent document generation system and method for the judicial field, relating to the field of document analysis technology. The generation method includes the following steps: performing structured analysis on historical judicial documents and extracting elements from the documents; establishing relationships between different elements; constructing a logical chain for the document based on the relationships between elements in any judicial document; comparing the logical chains of different judicial documents and identifying elements that exclude logical chains; generating relevant legal provisions matching the elements based on real-time collected case elements and logical chains; identifying the most applicable provisions and generating an initial document based on the exclusion of logical chains; evaluating the confidence level of each element in the initial document; optimizing the text of the initial document based on the evaluation results and providing risk warnings for potential elements; thereby improving efficiency while ensuring the professional quality and judicial security of the final document.

The application provides a kind of based on machine learning's tender document analysis processing system and method, through multi-channel receiving clarification request submitted by tenderer and uniform collection;Clarification request is text preprocessed, text features are extracted in combination with natural language processing (NLP) and machine learning technology, key problems and problem types are identified;Similar cases in historical database are retrieved based on problem features, and a candidate set of reference answers is generated;The optimal reference answer is filtered and pushed through confidence calculation, and the interaction details are recorded to form structured knowledge points;Model parameters and processing procedures are iteratively optimized based on knowledge points. Using the scheme of the application, automated and efficient processing of clarification requests can be achieved, reducing manual intervention, avoiding message omission, improving response speed and professionalism, and forming a reusable knowledge system.

This invention discloses an intelligent analysis and management system for certificates of conformity based on evidence collaboration, comprising a document analysis module, an evidence collaboration module, a trusted evidence storage module, a business linkage module, and a visualization governance module. The document analysis module performs structured analysis of certificate images and generates field content and confidence levels. The evidence collaboration module establishes and verifies the correspondence between certificates of conformity and physical products based on RFID / NFC tags, production chain data, and environmental chain data. The trusted evidence storage module uses blockchain technology to write operation records into a trusted ledger, achieving end-to-end evidence storage. The business linkage module automatically triggers business processes such as warehousing, release, and review based on consistency scores and on-chain compliance status, and records business behaviors. The visualization governance module constructs an event timeline and entity relationship diagram, providing comprehensive data presentation and traceability. This invention achieves integrated management of certificate of conformity information, improving the accuracy, reliability, and traceability of certificate of conformity management.

This invention discloses a method and system for extracting meta-analysis literature based on graph-anchored multi-agent systems. The method includes reconstructing unstructured PDFs into a hierarchical semantic document structure through visual document analysis and identifying functional area labels; applying functional area anchoring constraints to limit information search to specified functional area nodes; scheduling a multi-agent collaborative extraction network consisting of a reconnaissance agent, a logic assembly agent, and an indicator retrieval agent; and completing experimental variable identification, logical mapping between treatment and control groups, and cross-paragraph indicator retrieval through structured message dialogue and multi-round collaboration; employing a neural symbolic hybrid engine, where semantics are parsed by a large language model and precise mathematical aggregation operations and dimensional conversions are performed by a deterministic symbolic computation engine; and generating a structured data matrix with inverted index pointers. This application achieves high-precision, zero-error, and traceable automated extraction of meta-analysis literature data.

The application provides a PDF document content recognition method and device, equipment and a storage medium, the method comprises the following steps: obtaining an access link of an unanalyzed document; downloading a target PDF document from an object storage service according to the access link; when the content area corresponding to the page type in the target PDF document is a text area, the content area is divided into a text area, a table area and an image area according to the page type corresponding to each content area; when the content area is a text area, the original text character sequence is extracted from the text area, and the semantic coherent paragraph text is generated by similarity calculation on the original text character sequence. Based on the cosine similarity, the application automatically divides the sentences with similar semantics in the text area into the same text block, so that the document analysis obtains semantic coherent and complete text content, solves the problem of broken text paragraphs after document recognition, and effectively improves the semantic coherence of the document content.

This application discloses a document analysis method, apparatus, device, and medium based on a retrieval-enhanced generation framework, applied in the field of document analysis technology. The method includes: extracting target information from parsed information obtained from parsing several unstructured documents to construct an initial knowledge graph; the target information includes table information, text information, relationships between table information and text information, and relationships between table information; the nodes in the initial knowledge graph include table-related nodes determined based on the table information; performing entity linking and node relationship reasoning on the initial knowledge graph to obtain a target knowledge graph; the entity linking operation includes identifying target entities pointing to the same real-world object in different documents to establish cross-document links; retrieving the target subgraph of the query request from the target knowledge graph, using a large language model and generating query results based on the target subgraph to achieve the analysis of unstructured documents. This method can improve the document analysis results and enhance accuracy.

The application discloses a kind of big language model enhanced emission trading knowledge graph construction method and system, it is related to machine learning field.The present application obtains the unstructured text data in the field of emission trading, carries out document analysis and text segmentation to text data, obtains standardized text fragment;Based on the field of emission trading adaptability prompt engineering guides big language model, carries out entity recognition and relationship extraction to the text fragment, obtains initial knowledge triple and processing, obtains high-quality knowledge triple;Text fragment is converted and constructs structured triple with high-quality knowledge triple and semantic vector fusion's bimodal knowledge representation;The bimodal knowledge representation is stored to graph database, and constructs the field of emission trading knowledge graph;Based on double-path retrieval, carry out retrieval and knowledge traceability to knowledge graph, realize the field of emission trading intelligent question and answer and knowledge application.The present application realizes the efficient conversion from unstructured data to structured knowledge.

The application provides a kind of protection device fixed value automatic checking method and device, listen to the serial data of hardware interface of protection device and the bluetooth document of bluetooth module;The first fixed value sheet is obtained by hierarchical analysis to serial data;The second fixed value sheet is obtained by document analysis to bluetooth document;The checking result is obtained by comparing the first fixed value sheet and the second fixed value sheet;If the checking result is consistent, trigger the printing instruction to instruct the printer to print the checked fixed value sheet and display the checked fixed value sheet on the screen.The application realizes the automatic comparison and linkage printing of fixed value data by listening and automatically analyzing the serial data and bluetooth document of protection device, breaks through the data barrier between device running data, electronic fixed value sheet and paper archive, effectively avoids the false detection and missed detection problems that may occur during manual checking, significantly improves the accuracy and efficiency of fixed value checking work.

The application discloses a kind of multi-agent cooperation methods based on retrieval enhancement's knowledge integration, specifically related to compliance audit question and answer technical field, document analysis agent splits compliance document into clause fragment and generates clause positioning mark, constructs knowledge unit and calculates evidence qualified score, and stores into knowledge unit library;Inquiry analysis agent forms structured inquiry representation, and retrieval agent retrieves accordingly and generates evidence package under the filter rearrangement of evidence qualified score in audit mode;Reasoning agent constructs integrated evidence graph based on evidence package and generates conclusion unit, and outputs candidate reply with reference drop point;Consistency check agent calculates support score and contradiction score and determines auditable conclusion strength, and output control or trigger closed-loop rectification process is carried out to reply.

This invention provides an information processing system, a control method, and a program related to document analysis that enables appropriate OCR processing. [Solution] In an OCR support system in which a client terminal 101, a scanner 102, and a file server 103 are connected to each other via a network 100, the client terminal, which is an information processing device, includes a receiving means for receiving a range specification for a document, a determination means for determining whether the range specified by the receiving means meets a predetermined standard indicating a size suitable for OCR processing, and a notification means for notifying the determination result of the determination means.

The present disclosure relates to a document comparison system (100) for comparing a first document (D1) with a second document (D2). The first document (D1) includes at least a first section having at least one first section entity (CEn), and the second document (D2) includes at least one second document entity (CEn). The document comparison system includes a processor (110) and a memory device (120). The processor is configured to identify the at least one first section entity (CEn ) in the first section of the first document (D1). The processor conducts a search of the second document (D2) to identify the presence or absence of one or more second document entity (CEn) corresponding to or equivalent to each first section entity (CEn) identified in the first section. The present disclosure also relates to a dictionary generating system; a document comparison method; a dictionary populating method; and non-transitory computer-readable medium.

This invention relates to the field of document parsing, providing a method, apparatus, device, and storage medium for parsing tender documents. It utilizes a large language model to dynamically segment and extract semantic features from tender documents in a knowledge base, obtaining segmented text vectors. Based on the semantic features of the segmented text blocks, a multi-dimensional index structure is established according to multiple segmented text vectors. Pre-defined parsing items are converted into query commands through a question-and-answer interface of the knowledge base. Based on the query commands, the target information is obtained using the large language model and the multi-dimensional index structure. Compared to existing technologies where manual or simple tools struggle to effectively integrate the relationships within tender documents, this invention uses a large language model to extract semantic features from the tender documents and leverages the semantic association capabilities of the large language model to intelligently match and analyze the parsed tender requirements with the knowledge base, providing strong support for accurate recommendations and decision-making assistance.

The application discloses a picture-text recognition and translation system based on semantic recognition, which comprises a document analysis module, an image local text recognition module, a context perception module, a translation instruction generation module and a picture-text reorganization module; the document analysis module can separate original picture-text mixed arrangement documents into continuous text sets and image region sets; the image local text recognition module can obtain local text segments and determine basic semantic vectors by processing the image region sets; the context perception module can calculate the semantic correlation degree S of the basic semantic vectors and each paragraph vector; the translation instruction generation module can generate translation input sequences; and the picture-text reorganization module can generate translated image sets through the visual attributes and position information of original image regions, and then obtain bilingual translation documents. The application can make full use of complete semantic contexts provided by document main texts by the context perception module to realize the translation of image local texts.

The application relates to a multi-modal structured processing and retrieval method for multi-type professional documents, which comprises the following steps: selecting a plurality of multi-format documents and converting the documents into PDF format files by using a general tool; performing layout and content analysis on the PDF format files by using a multi-modal document analysis model to obtain semi-structured document data; performing data preprocessing on the semi-structured document data to obtain structured document data; dividing the structured document data based on a content subdivision strategy to obtain knowledge units, and storing the knowledge units in a retrieval database after data indexing and metadata labeling; searching the database according to a keyword to obtain an accurate evidence set of the content to be searched; inputting the accurate evidence set into a large model to output a response result about the content to be searched by the user. The application can solve problems such as mixed multi-format files, rich embedded objects, dense tables and formulas, and insufficient structure specification.

To perform accurate document analysis while accommodating the user's work skills. [Solution] A document analysis support device 1 comprises a storage device that stores a history of queries, which are data previously entered by a user requesting a trained model to analyze a document; and a computing device that performs an knowledge level determination process to estimate the user's level of knowledge regarding the document based on the changes in the entered queries; and an analysis process that obtains text specifying the document analysis method according to the level of knowledge, and inputs a prompt containing the obtained text into the trained model to output information of the document analysis results to an output device.

The application discloses a document analysis method and device, computer equipment and a readable storage medium, comprising: obtaining a to-be-analyzed document, and converting each page in the to-be-analyzed document into a page image; sequentially traversing each page in the to-be-analyzed document; performing vector judgment on the currently traversed page to obtain a vector judgment result for representing whether the page is a vector page or a non-vector page; calling an information extraction algorithm matched with the vector judgment result to extract text information of the page; inputting the page image corresponding to the page into a preset layout analysis model to enable the layout analysis model to output position coordinates and category labels of each layout area in the page image; generating a page analysis result of the page based on the extracted text information and the output position coordinates and category labels of each layout area; and after traversing all the pages, generating a document analysis result of the to-be-analyzed document based on the page analysis results of the pages.

The application discloses a research report generation method and electronic equipment, relates to the computer technical field, carries out multi-modal content structured extraction to the uploaded document, forms a structured document tree and stores into a vector database; the document key information is retrieved from the database, the document key information is filled into the corresponding task decomposition template, and the research outline is generated after adaptive adjustment; knowledge gap is identified, the optimal execution scheme is determined in combination with the task priority and information demand characteristics; the task is decomposed and iterative retrieval is executed, information is retrieved from the database and external resources to fill the knowledge gap, and the iterative convergence condition is judged through information entropy change and multi-round gain threshold; after judging the iterative convergence, the analysis results generated by the multi-round iteration are integrated and optimized in stages. In this way, the document analysis and report writing efficiency can be improved, the research report with deep thinking is output, the knowledge gap is actively filled, the human limitations are avoided, and the analysis results are comprehensive and accurate.

We provide the system. [Solution] A speech recognition means that receives audio data and converts that audio into text, A method for analyzing the flow, tempo, and timing of speech from text, A means of receiving presentation materials and analyzing the layout and content of the materials using image recognition technology, A means of integrating the results of audio analysis and the results of document analysis to generate feedback, A system that includes means for sending generated feedback to a terminal.

This invention discloses a cold chain logistics document analysis method based on multimodal and dynamic correlation, comprising the following steps: constructing a cold chain logistics document thesaurus and manually annotating the subject keywords of preprocessed cold chain logistics documents; constructing an analysis model, which includes a keyword extraction module, a ranking module, a temporal enhancement module, a business feature module, and a technical feature module based on a latent Dirichlet allocation word vector model; obtaining subject keywords that integrate temporal, business, and technical features based on manually annotated subject keywords; constructing a loss function and optimizing the parameters of the constructed analysis model by using a preset label minimization loss function; and constructing a dynamic correlation analysis between business and technical subjects. This method provides quantitative decision support for prioritizing technology investment, providing supply chain risk warnings, and determining business innovation directions in the cold chain logistics field, significantly improving resource allocation efficiency and policy response speed.

The application provides a multi-modal based document analysis method and device, relates to the field of unstructured data processing, and comprises the following steps: performing multi-modal analysis on a received unstructured document to obtain document content and corresponding content labels; performing tree structure construction on the document content and the corresponding content labels according to a preset financial system document structure to obtain a directory structure tree; converting the directory structure tree into a knowledge graph, and performing document content retrieval based on the knowledge graph. The application can conveniently and efficiently analyze system documents and provide a convenient and accurate system retrieval approach.

The system according to this embodiment aims to conduct fair and objective recruitment based on the skills and aptitudes of candidates. [Solution] The system according to the embodiment comprises a document analysis unit, an interview support unit, an answer analysis unit, and a job offer decision unit. The document analysis unit analyzes the candidate's documents. The interview support unit generates interview questions based on the results analyzed by the document analysis unit. The answer analysis unit analyzes the candidate's answers based on the questions generated by the interview support unit. The job offer decision unit makes a job offer decision based on the results analyzed by the answer analysis unit.

The application provides a kind of multi-modal adaptation device for low-resource multilingual document analysis, comprising: visual encoder, by progressive block merging, image is hierarchically encoded, a set of feature maps is generated, and projection and spatial alignment are carried out, to generate the visual feature map of uniform space grid, while extracting page-level description vector through global average pooling;Adaptive visual-text mapping module, the visual feature map is decomposed into horizontal, vertical, diagonal and global four kinds of anisotropic representation, the gate weight of four direction branches is dynamically calculated according to the description vector and language embedding, the dynamic weighting of fusion features is realized, and the visual feature embedding is obtained by mapping the fusion features to the decoder embedding space;Autoregressive multilingual decoder, by adding separable two-dimensional position coding in visual feature embedding and flattening as sequence as visual prefix, combined with task prompt word containing language identifier, task type, output format and optional spatial prompt, to generate output.

The present invention relates to a document analysis system that utilizes artificial intelligence to analyze documents written by group members in their daily lives, extract the key emotions and key keywords of the document writer, and determine relationships among group members. By utilizing the extracted key emotions and key keywords, the system analyzes and intuitively presents whether certain members are connected as a group or close companions, or whether certain members are isolated and not interacting with others.

A video manual generation device includes a document analysis unit, a video analysis unit, a link information generation unit to collect first sets each being a set of a noun and a verb from text information data, to collect second sets each being a set of an object and an action from object information data and action information data, to search those sets for a first set and a second set in which the noun and the object correspond to each other and the verb and the action correspond to each other, and to generate link information data indicating correspondence between a position in the work procedure where the first set obtained by the search is described and a scene in a video that includes the second set obtained by the search, and a video manual generation unit to generate video manual data based on the link information data.

For semantic content fingerprinting of textual content, a document analysis is performed on the textual content by using a generative pre-trained transformer (GPT) to obtain one or more semantic content features (SCFs) of the textual content, where each SCF includes one or more semantic facts about the textual content, and each semantic fact includes one or more words that describe the textual content. Further, a transformation resilient signature (TRS) of the textual content is created, where the TRS includes the one or more SCFs of the textual content. Such a TRS of textual content can prevent the textual content from being plagiarized and used without authorization.

The application discloses a kind of based on engineering cost knowledge graph's bidding document analysis method, this method is by to the cost knowledge graph generation of tender document and bid document, obtains tender knowledge graph and bid knowledge graph;Tender knowledge graph and bid knowledge graph are carried out multi-level node mapping matching, obtain several associated edges and the association score of each associated edge;Associated edge is the connecting edge between the first node and the second node of successful matching;First node is the tender parent node in tender knowledge graph or the tender subnode of tender parent node subordinate;Second node is corresponding with first node, and is the bid parent node in bid knowledge graph or the bid subnode of bid parent node subordinate;According to all associated edges and association score, carry out multidimensional analysis processing, obtain bidding document analysis result.The method can effectively improve the comprehensiveness and accuracy of bidding document analysis.The application relates to the field of data processing technology.