106 results about "Analysis Documentation" patented technology

The invention relates to the technical field of medical data management, in particular to a medical data document classification and marking system which comprises a document structure analysis module, a semantic information identification module, a classification and marking module and a document intelligent label module. According to the method, document visualization and retrieval efficiency is improved by analyzing document content and extracting titles, texts and appendixes, analytic performance and operability of data are enhanced by identifying key information and semantic relations and accurately extracting and labeling medical terms, medicine research data and medical record records, storage is optimized according to priorities in combination with classification and marking, and the method is high in practicability and easy to popularize and use. Clinical values and application scenes of documents are clarified, document management processes are refined, management compatible with clinical data formats is formed through structured storage of marked data and classification label generation, storage normalization and retrieval efficiency are improved, the requirement for accurate information calling in clinical tests is met, document management capacity is improved, and the document management efficiency is improved. And support is provided for improvement of clinical decision-making and research efficiency.

The invention discloses a document analysis and query method based on a knowledge graph, and the method comprises the steps: carrying out the part-of-speech tagging of a received to-be-analyzed document, and obtaining a part-of-speech tagging result; extracting knowledge element information from the part-of-speech tagging result based on a preset power grid domain ontology knowledge base, and constructing an initial knowledge graph based on the knowledge element information; combining nodes in the initial knowledge graph to obtain a fused knowledge graph; constructing a mapping table according to the fused knowledge graph, and generating a candidate query template set based on the mapping table; receiving a natural language query statement input by a user, selecting a target query template from the candidate query template set based on the natural language query statement, and generating a target query statement; querying from the fused knowledge graph by using the target query statement, and outputting a query result; according to the method, the accuracy and comprehensiveness of information analysis can be effectively improved, the query intention of the user can be accurately understood, and the accurate query and analysis requirements of professionals on project documents are met.

A document is analyzed to identify attributes of the document. A set of statistical measures are calculated for each of the formatting attributes. A correlation between these statistical measures and elements of the document are identified. A hierarchical relationship is determined between the elements of the document. Data from the document is split into chunks using the hierarchical relationship. A representation of the document that includes the hierarchical structure is then generated. The representation is stored in a data store as a vector usable by a machine learning model to perform a query on the document according to the hierarchical structure.

Provided is a cyber threat information processing method including receiving a CTI analysis request for a document script included in a file from a client; analyzing the document script to obtain analysis information of the CTI for the document script; generating a CTI query related to the document script based on the analysis information of the CTI and delivering the CTI query to a natural language model; and providing natural language description information according to the CTI query from the analysis information of the CTI and the natural language model to the client as visualization information.

A data processing system implements obtaining an image of a document and an indication of one or more content items to generate; analyzing the image of the document to generate a textual representation of contents of the document in the image; constructing a query based on the textual representation; analyzing the query using a second machine learning model to obtain embeddings representing one or more categories of information represented in the query; searching a knowledge graph based on the query embeddings to obtain results of the query; providing the query results to a content generation unit to generate the one or more content items based on the results of the query; and obtaining the one or more content items from the content generate unit.

The invention relates to the technical field of issuing management, in particular to an international standardization organization file issuing management system and method, and the system comprises a document content auditing module, a permission dynamic adjustment module, a manual auditing distribution module, a manual operation auditing module, a standard reference updating module and a file issuing module. According to the method, the standardization and accuracy of the file are ensured by analyzing the deviation between the format and the structure of the file, the auditing efficiency and the auditing quality are improved by distributing the file to the auditing personnel with the matched authority and performing priority ranking based on the sensitivity of the file type, and the auditing efficiency and the auditing quality are improved by monitoring the file revision operation and identifying the abnormal operation behavior. According to the file issuing management method and device, the safety and traceability of the file are improved, the timeliness and accuracy of the file content are ensured by updating expired and wrong content reference, the file issuing management efficiency is effectively improved, the risk of human errors is reduced, and accurate transmission and compliance of information are ensured.

The following relates generally to using generative AI to: (i) classify documents; (ii) generate prompts to classify documents; (iii) evaluate the classification performance of prompts; (iv) generate updates to prompts; and / or (v) train classifiers. In some embodiments, one or more processors: generate a prompt for input to the generative AI model; generate classifications for a set of documents from the corpus of documents by inputting the set of documents and the prompt to the generative AI model; based on the classifications, provide the set of documents to a review platform for manual review by a reviewer; obtain review data associated with a subset of documents from the set of documents; and train, by executing a training algorithm, a classifier using the review data as ground truth data, wherein the training algorithm is configured to analyze extracted relevant document portions of the subset of documents to train the classifier.

The invention discloses a document recognition method and device, related equipment and a computer program product, a to-be-recognized text can be split into multiple pages of document images, the visual features of each page of document image are extracted respectively, the visual features of the multiple pages of document images can be sent into a large model at the same time, and the recognition efficiency is improved. Meanwhile, text features of a first document recognition instruction are extracted and sent to the large model, the first document recognition instruction is used for indicating the large model to output the document recognition result of the document image, and therefore the recognition result of the multi-page document can be output end to end through the large model. The large model has stronger modeling capability, and meanwhile, the visual features of the multi-page document images are sent into the large model, so that context information among different pages of document images can be reserved, context semantics of a text can be understood, and a hierarchical structure and a content relationship of the document can be analyzed more accurately; therefore, the accuracy of text recognition and layout understanding is improved, and the accuracy of the recognition result of the multi-page document is improved.

The invention provides a rapid office document arrangement method, medium and system, and belongs to the technical field of document arrangement, and the method, medium and system comprises the following steps: analyzing a mark of a document, and constructing original feature data; constructing a feature processing model; constructing a contribution degree evaluation model to analyze the contribution degree value of the layout element in the document to the document typesetting score; obtaining a contribution degree evaluation model through training; determining a layout priority level and a layout interval value according to the contribution degree value; generating a mark tree of the document; performing dimension reduction mapping on the document feature vector and mapping the document feature vector to a three-dimensional display space to generate a three-dimensional layout mapping model; according to the method, the multi-modal features of the document can be comprehensively analyzed, the contribution degree of each layout element can be predicted, the optimized document layout can be generated, the rendering efficiency can be improved, and the problem that the layout quality is difficult to guarantee at present, and the layout efficiency of the document can be improved is solved. And the rendering performance is improved.

Various embodiments disclosed relate to a method of producing an analysis document using generative artificial intelligence, the method comprising: maintaining a database containing multiple language learning models and a collection of prompts; generating a patent prosecution tool user interface integrated with a generative artificial intelligence program; receiving a user input comprising a matter associated with at least one matter dataset, where the matter dataset includes a plurality of patent documents associated with the matter; selecting a language learning model from the database; retrieving a plurality of patent documents for display on the patent prosecution tool user interface; loading at least one of the plurality of patent documents into the artificial intelligence program; displaying more than one prompt from the collection of prompts; initiating a script in the generative artificial intelligence program based on a user selected prompt and the at least one patent document; analyzing the patent document according to the script to produce a preliminary analysis; producing the analysis document according to the preliminary analysis; saving the analysis document.

The invention discloses a document-based business processing method and device, equipment, a storage medium and a program product, which can be applied to the field of financial science and technology. The method comprises the steps of obtaining a to-be-analyzed ESG document of a to-be-evaluated enterprise, and performing text preprocessing on the to-be-analyzed ESG document to obtain target ESG text data; inputting the target ESG text data into a pre-trained named entity recognition model to obtain a vocabulary sequence set output by the model; performing vocabulary analysis on each entity vocabulary in the vocabulary sequence set, and determining an ESG association index in each entity vocabulary; performing index feature analysis on the ESG association index, and determining an ESG evaluation result of the target enterprise; and performing business processing on the target enterprise according to the ESG evaluation result of the target enterprise. According to the technical scheme, the accuracy and comprehensiveness of identifying and evaluating the ESG document are improved, and the accurate processing of related business of an enterprise is realized.

A system for analyzing documents to be used for verifying a system-on-a-chip (SoC). The system includes: a parser configured to analyze a technical document associated with the SoC to generate multiple text fragments; a data preparator configured to convert the multiple text fragments into a dataset for a machine learning model; and a machine learning model block configured to perform a training mode including multiple training epochs or an inference mode. In each training epoch, the machine learning model block trains the machine learning model based on the dataset such that a label is appended to each text fragment. In the inference mode, the machine learning model block makes a prediction for each text fragment based on the training result to generate the dataset with prediction values.

The invention discloses a multi-source heterogeneous information extraction and structured processing method based on natural gas business data, and relates to the technical field of artificial intelligence application in the energy industry, and the method comprises the steps: analyzing a multi-modal document: carrying out the content analysis of natural gas sales documents in various formats, extracting key information, and obtaining the analyzed original data; data preprocessing: cleaning, recombining and standardizing the data to obtain preprocessed data; the mixed information extraction comprises key business index extraction, field rule base establishment, mixed extraction model establishment and context reasoning, and missing items in data are complemented by analyzing overall information and local content of a document, so that the integrity and accuracy of the information are improved; performing intelligent post-processing and constructing a relational database; according to the processing method, the natural gas service data can be accurately and efficiently extracted from the documents in various formats, and a basis is provided for subsequent data analysis and decision support.

A method for managing computer aided design (CAD) documents is disclosed. In some embodiments, the method includes generating a signature corresponding to a CAD document including a set of regions. The method further includes analysing the CAD document based on the signature and an associated document type. The method further includes categorizing each of the set of regions into one of a set of pre-defined classification categories based on the analysis. The method of further includes generating feedback corresponding to each of the set of regions based on an associated classification category of the set of pre-defined classification categories, upon categorizing. The method further includes rendering the feedback associated with one or more regions of the set of regions based on user requirements.

Document analysis systems and methods for the generation of a content-by-example log that expresses withheld documents in terms of a set of disclosed documents are disclosed. Additionally, document analysis systems and methods for the analysis of such a content-by-example log to determine withheld documents of interest without access to those withheld documents are disclosed.

A global segmenting and analysis service of a provider network may receive documents (e.g., posts, product reviews) from different applications. The service may analyze the documents to identify target entities and sentiment. The service may generate different levels of sentiment data and store data into a segmented database. For example, the service may store within-document level sentiment, document-level sentiment, and multi-document level sentiment for a target entity. The service may also update the entity taxonomy automatically or with only a small number of sample documents. The client may query the service for the segmented sentiment data.

The invention relates to the technical field of artificial intelligence, in particular to a method and a framework for optimizing scanning copy content recognition quality by using a large model. The method comprises the steps of document image analysis and processing, character extraction and formatting and context-based OCR correction by using a large model. The invention aims to provide the method and the framework for optimizing the identification quality of the scanned copy content by using the large model, the powerful functions of large language models such as a visual model and a text model are combined, the deep understanding of the document content and layout is realized, the document layout is accurately analyzed, different elements such as text blocks, tables and images are identified, and the identification quality of the scanned copy content is improved. And in combination with an analysis result of the visual model, converting the document content into a graceful and smooth Markdown format, and retaining an original layout of the document.

To provide systems and methods for Extensible Business Reporting Language (XBRL) tag suggestion and validation.SOLUTION: The present invention provides a method that includes the following steps: (230B) receiving an XBRL document associated with one or more assigned XBRL tags; (240B) analyzing the XBRL document using a trained machine learning model to generate one or more suggested XBRL tags and determine one or more corresponding confidence values; (245B) comparing the one or more assigned XBRL tags with the one or more suggested XBRL tags to generate comparison results; and (250B) determining a tag confidence value associated with each assigned XBRL tag of the one or more assigned XBRL tags based on the comparison results.SELECTED DRAWING: Figure 2B

Document analysis systems and methods for the generation of a content-by-example log that expresses withheld documents in terms of a set of disclosed documents are disclosed. Additionally, document analysis systems and methods for the analysis of such a content-by-example log to determine withheld documents of interest without access to those withheld documents are disclosed.

A computing platform performs automated due diligence by acquiring project scope information and documents, standardizing all data across all document types into a uniform format optimized for analysis and subjecting the data to repeated querying by large language model agents to triangulate it against a body of human content expertise coded into the platform. The platform compares variables with a project proforma, verifies permits by parsing permit data and cross checking a permitting authority portal, evaluates design completeness by detecting standards of readiness status, and measures the bankability of project agreements compared to industry standards. The platform computes environmental, social, and governance metrics, assesses counterparty risk and community sentiment using searches of public sources, and validates a reported capital stack by analyzing documents and applying industry standards thereto. The platform calculates risk metrics, applies weights to produce two scores, and generates a report that includes remediation steps.

A computer-implemented method, system and computer program product for identifying equivalent technical terms. A deep learning model is trained to identify equivalent technical terms. The deep learning model is then applied to a new document. The sentences of the document are analyzed to identify technical terms. Text is then analyzed surrounding the technical term identified in the document to determine the meaning of such text. A glossary list is then reviewed to determine if the identified meaning of the analyzed text matches a meaning / concept in the glossary list linked to a technical term. In response to determining that the meaning of the analyzed text matches a meaning / concept in the glossary list linked to an equivalent technical term, the technical term in the document is annotated with the equivalent technical term. In this manner, non-standard equivalent technical terms in different documents with the same meaning / concept are able to be identified.

The invention provides a method and device for code analysis, electronic equipment, a computer readable medium and a computer program product. The method comprises the following steps: performing code analysis on a target code to obtain multi-dimensional structured information of the target code; converting the obtained structured information into context information which can be understood by a large language model; performing semantic understanding and intention inference on the context information by using a large language model; and generating analysis result information of the target code based on the semantic understanding and intention inference results. According to the method, through multi-dimensional code analysis, grammar analysis and deep semantic understanding are remarkably improved, and the generation quality of a code analysis document is greatly improved; code logic and design intention are deeply understood by using a large language model, high-quality technical documents are automatically generated, and the intelligent level of code analysis is remarkably improved.

Document analysis systems and methods for the generation of a content-by-example log that expresses withheld documents in terms of a set of disclosed documents are disclosed. Additionally, document analysis systems and methods for the analysis of such a content-by-example log to determine withheld documents of interest without access to those withheld documents are disclosed.

Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.

The invention discloses a message difference risk identification method and device, equipment and a storage medium, and relates to the technical field of risk identification, and the method comprises the steps: obtaining a target to-be-analyzed document pair which comprises a first to-be-analyzed document and a second to-be-analyzed document; based on a graph neural network model, performing difference analysis on the first to-be-analyzed document and the second to-be-analyzed document to obtain a difference analysis result, the graph neural network comprising a graph encoder constructed based on graph convolution operation; and based on the difference analysis result, carrying out risk analysis on the target to-be-analyzed document pair to obtain a risk analysis result. According to the invention, a more accurate risk analysis result can be provided.

Systems and methods for analyzing documents are provided herein. A plurality of documents and user input are received via a computing device. The user input includes hard coding of a subset of the plurality of documents, based on an identified subject or category. Instructions stored in memory are executed by a processor to generate an initial control set, analyze the initial control set to determine at least one seed set parameter, automatically code a first portion of the plurality of documents based on the initial control set and the seed set parameter associated with the identified subject or category, analyze the first portion of the plurality of documents by applying an adaptive identification cycle, and retrieve a second portion of the plurality of documents based on a result of the application of the adaptive identification cycle test on the first portion of the plurality of documents.

A document management system analyzes document clauses using document clause clusters. The document management system uses measures of similarity between document clauses from different documents to assign clauses to clause clusters. Clause clusters may be used to perform various analyses, such as to assign clauses a classification corresponding to a relevant clause cluster. The document management system provides analyses performed using document clause clusters for user review, such as to approve clause clusters, classify clause clusters, modify clause clusters, or some combination thereof.

The invention discloses a document processor based on artificial intelligence (AI), which belongs to the technical field of artificial intelligence and natural language processing, and comprises an input module used for receiving documents from various sources; the preprocessing module is used for carrying out format unification and preprocessing operation on the input document; the document analysis module is used for analyzing documents by using a natural language processing technology and a computer vision technology; a document classification module; a multi-modal analysis module; a semantic map construction module; the information extraction module is used for extracting key information in the document; an information editing module; a document temporary storage module; an output module; and a user interface module. According to the method, key information such as texts, images and table contents can be rapidly and accurately extracted from massive documents, data can be rapidly identified and sorted, complexity and errors caused by manual extraction are avoided, accurate and timely data support is provided for enterprise decision making, and the working efficiency and decision making scientificity are greatly improved.

The invention discloses a public opinion detection and analysis system, and relates to the technical field of public opinion detection and analysis, and the system comprises a word-meaning connection module which is used for constructing a word-meaning connection tree of words, a root node is any word, child nodes are words related to the root node, values are assigned to the child nodes according to a co-occurrence frequency, and the sum of the values of all the child nodes is one; the semantic connection module is used for constructing a word meaning connection tree of each child node by taking the child node of the word meaning connection tree as a root node until a preset layer number is reached, so as to obtain a semantic connection tree; and the keyword detection module is used for performing matching analysis on the to-be-analyzed document and the semantic linkage tree of the keywords to obtain a public opinion keyword set of the to-be-analyzed document. By constructing a word association tree, a co-occurrence frequency matrix and a multi-level similarity matching calculation model, high accuracy, dynamic adaptability and high robustness of keyword recognition are achieved, and keyword recognition precision and stability in a complex context are improved.

The present invention discloses a device (100), a system (200), and a method (300) for analysing a document received from one or more users. The invention includes a system (200) for document analysis. The system (200) comprises a user interface (101) to interact with users. The user interface (101) generates queries and receives documents from users. The documents are then transmitted to a device (100) equipped with processors (102) for analysis. The processors (102) extract key sections from the document, prioritize them, remove noisy data, and generate a summary. An interactive tool (105) within the user interface (101) facilitates user feedback on the analysis. The user feedback is used to update a keyword dictionary (104) at predetermined intervals, allowing the system (200) to continuously improve its document analysis capabilities.