46 results about "Document quality" patented technology

The invention discloses a document generation system and method based on multi-agent collaboration, and the method comprises the steps: understanding and extracting the high-level semantic information of a text input by a user, and dynamically generating a problem to guide the user to define a demand, so as to form a detailed document demand; recognizing the theme and key elements of the document from the detailed document requirements; the optimal sequence of task execution is determined based on a shortest path algorithm, potential conflicts in task execution are predicted and solved through parallel processing and a search algorithm, and optimized task planning is formed through feedback circulation; generating a document outline according to user requirements, retrieving associated contents of document chapters so as to write chapter contents, and performing grammar and format verification to form a preliminary document; defining a document quality evaluation index according to user requirements and industry standards, performing document quality evaluation on the preliminary document, and feeding back the document quality evaluation result to the user; and generating a complete final document and presenting the complete final document to the user. According to the invention, the document generation quality is improved.

The invention discloses a self-adaptive text extraction method and system based on artificial intelligence, and the method comprises the steps: carrying out the analysis of the document structure entropy of an example document set, quantifying the noise density, geometric distortion degree and background complexity of the example document set, and carrying out the self-adaptive selection of a preprocessing assembly line intensity grade according to the above; dynamically configuring image preprocessing parameters and AI recognition model parameters, and generating a recognition engine instance to output a preliminary recognition text; after regularized coarse screening extraction is carried out based on key field description, a multi-candidate generation strategy is started for low-confidence-coefficient candidate text fragments, a multi-person cooperative verification process is triggered for lower-confidence-coefficient fragments, finally all the fragments are processed through a text standardization module, and structured text extraction information is output. According to the method, accurate adaptation of processing intensity is achieved through document quality quantitative evaluation, the extraction accuracy and system robustness of complex heterogeneous documents are effectively improved through a multi-level confidence coefficient verification mechanism, and the identification error risk caused by image quality fluctuation or rule solidification is reduced.

The invention discloses an archive document quality evaluation method and an archive document quality evaluation system based on ConvNeXt V2. According to the method, an improved ConvNeXt V2 model is used for carrying out character density classification on a preprocessed archive document image, and probability distribution is output. Meanwhile, the quality evaluation model of the OCR text-image double-branch structure is adopted to evaluate the quality of the image. The OCR text branch uses a ViT model and a transpose attention module to extract visual features and calculate a document stream score; according to the image branch, image features are extracted by using a convolutional neural network and ResNet, global multi-scale features are formed through residual connection, and an image flow score is calculated. And finally, fusing the image flow score and the document flow score through double-flow dynamic weight to obtain an image quality evaluation score. According to the method, the model architecture is improved, and the dynamic weight algorithm is designed, so that the classification and quality evaluation of the archive document image are improved.

The invention provides a large model data set quality evaluation method and system. The method comprises the following steps: S1, constructing a large model data set quality evaluation framework based on file quality, file description quality, file content quality, data labeling quality and model training quality; s2, constructing a large model data quality evaluation index based on the constructed large model data set quality evaluation framework; and S3, acquiring a large model data set, classifying the large model data set according to modal types and single evaluation indexes, and performing corresponding quality evaluation on the classified data set. According to the method, the data set quality of the large model can be comprehensively and systematically evaluated, and the high-quality data set construction of the large model can be effectively guided, so that the training efficiency of the large model is improved, errors and deviations in the training process are reduced, and the accuracy and generalization ability of the model are improved.

The invention relates to the technical field of bidding information processing and document auditing, and discloses an intelligent bidding document quality evaluation and auxiliary generation system based on multi-dimensional detection, and the system comprises an information extraction module which is used for analyzing a bidding document file and extracting various nodes; the knowledge graph construction module is used for receiving the nodes and constructing a response evidence chain type knowledge graph; the risk assessment module is used for identifying a response path in the knowledge graph, judging a path mode and calculating a quantitative risk score; and the report generation module and the auxiliary generation module are used for generating a bidding document quality evaluation report containing specific modification suggestions according to the risk evaluation result. According to the method, a traditional manual auditing process is automated, multi-dimensional detection means such as text analysis, image detection and external credit query are comprehensively applied, quantitative evaluation of bidding response risks, accurate positioning of high-risk items and automatic generation of modification suggestions are achieved, and therefore the efficiency, depth and accuracy of bidding document quality auditing are improved.

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 application discloses a kind of legal document quality confrontation test method based on logic game, it is related to legal artificial intelligence technical field, including, collection legal document full-text data, and extract fact triple, evidence citation fragment, law article number and conclusion claim, generate structured argumentation set;Based on the confidence attenuation sequence of multiple rounds of game, in combination with the vulnerability propagation coefficient corresponding to different types of edges in directed heterogenous graph, carry out path vulnerability contribution value calculation, and generate legal document global vulnerability index by stratified accumulation;Based on logic breakpoint list, contradiction conflict list and legal document global vulnerability index, comprehensive evaluation legal document's logic integrity, argumentation consistency and conclusion robustness, generate structured check report.The application provides a complete and feasible implementation path for the automatic check of legal documents combined with natural language processing.

The invention provides an intelligent official document checking system and method based on AI drive, a storage medium and electronic equipment, and the system comprises a data layer which is used for collecting, storing and preprocessing official document data, and the official document data comprises various standard official document templates, historical official document data and official document processing standard files; the algorithm layer is integrated with a natural language processing module, a machine learning module, a knowledge graph module and a deep learning module and is used for identifying, analyzing and judging official document data; the application layer is used for constructing a format specification checking module, a content quality checking module and a sensitive information screening module based on the algorithm layer; and the interaction layer is used for interacting with a user, receiving an official document uploaded by the user and outputting a verification result to the user. The system provided by the invention can improve the administrative efficiency, improve the document quality, reduce the administrative cost and guarantee the information security.

The invention provides an intelligent quality assessment document generation system with a triple collaborative structure, and the system comprises a coordinator module which is used for receiving user input, accessing an NQI knowledge base module, analyzing demands, determining quality dimensions and indexes, and generating a document frame; the worker module is used for receiving the document framework, generating index content and completing content creation to obtain a first document; the supervisor module is used for receiving the first document, calling the document quality evaluation agent module for evaluation and generating a feedback report; and the feedback optimization processing module is used for receiving the feedback report, triggering optimization measures and evaluating the quality of the optimized document to obtain a final document. According to the technical scheme, efficient, accurate and intelligent quality evaluation document generation is realized.

The present disclosure provides a document quality evaluation method and device, electronic equipment and medium, relates to the technical field of computers, in particular to the technical field of artificial intelligence and machine learning. The implementation scheme is: obtaining a plurality of document data of a target document; obtaining a document feature vector of the target document based on the plurality of document data; and performing predictive analysis on the document feature vector to obtain a quality score of the target document.

The invention discloses a document generation method and device, equipment and a medium, and relates to the field of artificial intelligence, and the method comprises the following steps: obtaining a document theme which is used for indicating theme content of a to-be-generated first document; obtaining a plurality of sample documents and a plurality of data contents, wherein the plurality of sample documents meet preset document quality requirements; determining at least one sample document from the plurality of sample documents based on the document topic, and determining a first data content from the plurality of data contents based on the document topic; performing format conversion on the first data content to obtain first chart content; analyzing the first chart content through a first natural language model, and outputting to obtain a first text content for describing the first chart content; analyzing the document theme, the at least one sample document, the first chart content and the first text content through the second natural language model, and outputting to obtain a first document. The document generation efficiency and the document quality can be improved.

According to the scholar cooperation influence assessment method based on dynamic contribution weighting provided by the invention, firstly, through fusion of multi-dimensional features such as scholar roles, participation degrees, technical contributions and time-varying reference approval, refined and dynamic measurement of scholar contributions in a single cooperative literature is innovatively realized; the limitation of static distribution according to a simple signature rule in the traditional method is broken through; combining the dynamic contribution weight with literature quality to construct a weighted scholar cooperation network which more accurately depicts cooperation strength and quality; on the basis, a network influence propagation model based on dynamic weighting is introduced, the direct contribution influence of scholars is calculated, and the indirect influence obtained through cooperative network propagation is quantified, so that the real influence of the scholars in an academic community is reflected more comprehensively; by integrating direct and indirect influences and introducing time decay and subject normalization processing, the finally output comprehensive influence index has both time sequence dynamics and interdisciplinary comparability.

A computer-implemented document evaluation system employs dual metrics combining an Intrinsic Document Quality Score (IDQS) and Comparative Document Score (CDS) for dynamic, context-aware evaluation across domains. The system addresses the cold start problem by immediately generating IDQS for new documents using Large Language Model evaluation of structured summaries that exclude author and source information to reduce bias. Documents are continuously re-ranked through pairwise IDQS comparisons, with CDS scores updated using zero-sum scoring. The microservices architecture with distributed processing enables scalable handling of large volumes. A matching algorithm selects document pairs for comparison based on similarity metrics using feature engineering. The approach improves computational efficiency by comparing IDQS values rather than full documents while maintaining content quality focus. The system provides immediate quality assessment and evolving comparative evaluation, offering comprehensive document ranking adaptable to different fields and document types.

The embodiment of the invention discloses an SPEC-based artificial intelligence document generation method and related equipment. The SPEC-based artificial intelligence document generation method comprises four SPEC stages including a demand analysis stage, an outline generation stage, a task planning stage, a content creation stage and the like. According to the SPEC-based artificial intelligence document generation method, through a standardized SPEC four-stage process and in combination with key technologies such as a cue word constraint mechanism, progress label analysis and format label analysis, the intellectualization of the creation process of documents, especially professional documents, is realized, and the creation efficiency and the document quality are remarkably improved; specifically, a document creation process is divided into four ordered stages including a demand analysis stage, an outline generation stage, a task planning stage and a content creation stage, so that staged management can be realized, parameters are finely controlled in each stage, and a document which is easier to meet user requirements is generated. The method is widely applied to the technical field of artificial intelligence.

The invention discloses a bidding document quality evaluation and model training method and device, equipment and a storage medium, and the method comprises the steps: obtaining sample bidding document data, carrying out the quality evaluation of a corresponding sample bidding document through a low-rank adaptive large model based on the sample bidding document data, and determining a relative advantage value based on the accuracy, simplicity, integrity and formattability of a quality evaluation result; adjusting low-rank matrix parameters of the low-rank adaptation large model based on the relative advantage value to obtain a teacher model; performing quality evaluation on the corresponding sample bidding document through the teacher model and the student model based on the sample bidding document data, and obtaining and determining training loss of the student model based on target intermediate feature representation and target evaluation result probability distribution generated during evaluation; and adjusting model parameters of the student model according to the training loss. According to the method, the lightweight bidding document quality evaluation model capable of stably, accurately and efficiently evaluating the bidding document quality can be obtained through efficient training.

The invention relates to the technical field of quality inspection, in particular to a CAD quality batch inspection method, which can utilize table tool software to call an inspection module to execute standard inspection, secondary development inspection and visual feature quantity statistics on CAD files, count the total error number and the total warning number according to the results, and calculate and output scores of the CAD files; sorting the CAD files according to the error number; and according to the inspection result, generating a structured report. It can be understood that according to the technical scheme, when mass CAD file quality inspection is carried out, the wanted quality inspection result can be obtained only by operating table tool software, and operation is convenient and fast; meanwhile, self-defined secondary development inspection items can be constructed on the basis of standard inspection items, and customized design specifications of different enterprises are adapted; the checking module is called for batch checking, and the output checking result is accurate; the efficiency of CAD quality batch inspection is improved, and the accuracy of parallel engineering is improved.

This invention relates to the field of engineering design technology, and in particular to a method and system for auxiliary design of nuclear power plant engineering modifications. A method for auxiliary design of nuclear power plant engineering modifications includes: acquiring multi-format design documents and structuring the content of these documents to obtain structured data with consistent format; establishing a hybrid engine using a first language model and preset rules; extracting nuclear power plant engineering documents using the hybrid engine to construct a tag library; segmenting the structured data and saving it in association with the tag library to construct a nuclear power knowledge base; training a second language model based on the nuclear power knowledge base to establish a domain-specific vertical model; acquiring design instructions and generating auxiliary information using the domain-specific vertical model. This invention significantly improves knowledge utilization by leveraging structured data and a nuclear power knowledge base; ensures professionalism and accuracy through the combination of a vertical domain model and the nuclear power knowledge base; and creates an intelligent auxiliary design process using design instructions, improving design efficiency and document quality.

The invention relates to the technical field of project file digital generation and management scheme design, in particular to a project file digital generation and management method and system and electronic equipment. The method comprises the steps of obtaining subitem project names of a target project; obtaining preset preposed data corresponding to each preset work task name of each subentry project; and generating a work file of each work task according to the obtained preset preposition data. The invention provides a comprehensive and systematic digital solution, and has the following remarkable beneficial effects of improving file quality, reducing personal errors, improving file generation efficiency, shortening a project period, optimizing version management, realizing whole-course tracing, supporting efficient cooperation of multiple persons, reducing communication cost, dynamically adapting to project requirements, and improving project quality. The method achieves the timely updating and maintenance of files, comprehensively covers the types of project files, meets the diversified demands, drives the decision through data, improves the project management level, promotes the digital transformation of the engineering industry, and improves the industrial competitiveness.

We propose a technology that accurately predicts future inquiry volumes, taking into account the specific circumstances of each software product. [Solution] This disclosure proposes a server device for predicting the number of future user inquiries for each function constituting a software product, which performs the following processes: obtaining past inquiry information from an inquiry information database and calculating a reference prediction value, which is a predicted value for the number of future inquiries for the function to be predicted, according to existing prediction techniques; and obtaining quality evaluation values ​​for documents related to the function to be predicted from a document quality database, modifying the reference prediction value based on the obtained quality evaluation values ​​for the documents, and calculating a first modified prediction value.

The invention relates to the technical field of intelligent document generation, and discloses an intelligent document generation system combining adaptive user interaction and natural language processing, which comprises an information acquisition module, an intention analysis module, a dynamic question and answer module, a content generation module and an optimization adjustment module. The system realizes multi-round dialogue management, context tracking and flexible question generation through a dynamic question and answer mechanism and a natural language processing technology, ensures comprehensiveness and accuracy of information collection, and improves document quality through grammar, style and logic optimization. According to the method, the problems that a traditional document generation tool is insufficient in flexibility, limited in semantic understanding and poor in interaction experience can be solved, personalized, high-precision and high-efficiency document generation is achieved, diversified requirements of users are met, and the user experience is improved.

Systems, methods, and storage media for providing a scalable platform for improving legal drafting efficiency using generative ai and expert-in-the-loop are disclosed. Exemplary implementations may: provide a platform that allows firms to request drafting services on an on-demand basis; provide, through the platform, a two-sided marketplace supporting the network of drafters; utilize advanced technology to minimize waste in the production of legal documents; implement strict document guidelines and quality assurance procedures to ensure a consistent quality legal documents; and provide a project dashboard and automated workflows to ensure projects stay coordinated and on-schedule.

The present application relates to the technical field of artificial intelligence, and provides a manuscript quality evaluation method, device, equipment, storage medium and program product, the method comprises: carrying out semantic segmentation on a source document to obtain a multi-ary semantic tree, each node in the multi-ary semantic tree contains the semantic vector of the corresponding text segment in the source document; the page sequence of the presentation corresponding to the source document is analyzed in multiple modes to obtain a page vector sequence; based on the similarity between each page vector in the page vector sequence and the semantic vector of each node in the multi-ary semantic tree, a page segment association matrix is constructed, realizing accurate semantic alignment from the document paragraph to the PPT page; based on the page segment association matrix, consistency quality evaluation is carried out, which can not only effectively identify whether the content is accurate, but also locate the specific deviation source, thereby significantly improving the accuracy and reliability of PPT quality evaluation, and providing strong technical support for the consistency check of PPT and source document in the office automation scene.

The application discloses a kind of legal document intelligent generation method and system based on large model, it is related to natural language processing technical field.The method is by legal relevant text and pre-processing through multi-channel acquisition, constructs legal domain knowledge graph, with BERT model pre-training and graph and document sample are fused and fine-tuning training;User selects document type and input parameter with the aid of interactive interface and transmits to model generation legal document first draft, again by multidimensional evaluation and optimization cycle, until the legal document of output standard is reached;The method covers data processing, knowledge graph construction, model training and document generation evaluation whole process, utilizes multi-source data and enriches knowledge reserve, and is combined with pre-training and fine-tuning to improve the pertinence of model, multidimensional evaluation guarantees document quality.Effectively solve legal document writing efficiency, quality is unstable and other problems, improve legal document generation efficiency and quality, promote the intelligent development of legal field.

A method and system of determining quality of a document image is disclosed that includes segmenting, by one or more processors, a document image into a plurality of regions each of which comprises text data. The plurality of regions is classified into one of a plurality of image quality classes based on a determination of a highest prediction value from one of a plurality of machine learning models. The plurality of machine learning models is trained corresponding to one of the plurality of image quality classes. A cumulative quality score for the image is computed based on a weighted average of a number of regions classified into each of the plurality of image quality classes. The quality of the image is determined based on the cumulative quality score.

The invention discloses a document quality detection and error correction system, and relates to the technical field of document detection, and the system comprises a quality detection module which is used for carrying out the structure analysis and content evaluation of an input document, and obtaining a quality detection result of the input document; the text error correction module is used for performing intelligent error correction on the input document through the term protection mapping table and the error pattern library to obtain a text error correction result of the input document; and the report integration module is used for integrating the quality detection result and the text error correction result of the input document into a quality evaluation report of the input document and outputting the quality evaluation report. Therefore, full-dimension quality detection and text error correction of the document structure and content are realized through the document quality detection and error correction system, so that the accuracy and semantic coherence of technical terms are ensured, the system is suitable for automatic quality detection and intelligent error correction of technical documents of multiple types, long texts and complex structures, and the document auditing efficiency and quality are improved.

The invention relates to the technical field of artificial intelligence, and discloses an evaluation processing method and device for a source document generated by retrieval, the evaluation processing method for the source document generated by retrieval comprises the following steps: analyzing the source document to obtain text information, structured information and format information of the source document; based on the text information, the structured information and the format information, performing multi-dimensional evaluation processing to obtain at least two of a structural integrity evaluation result, a content definition evaluation result, a context independence evaluation result and a format normalization evaluation result of the source document; and weighting at least two of the structural integrity evaluation result, the content definition evaluation result, the context independence evaluation result and the format normalization evaluation result to obtain a comprehensive evaluation result of the source document. Through the method, intelligent analysis can be performed on the Word document, and quantitative evaluation is performed on the Word document from multiple dimensions of structure, content and format, so that the document quality is improved.

The application discloses a kind of operation and maintenance document quality determination methods, comprising: determining reference data of operation and maintenance document in different quality evaluation dimensions;According to the reference data of different quality evaluation dimensions, determine the result information for measuring the quality of operation and maintenance document;Wherein, the different quality evaluation dimensions include one or more of structural integrity dimension, easy to execute dimension, specification dimension, effective dimension, easy-to-read dimension and basic quality dimension;The operation and maintenance document is the document indicating the operation and maintenance strategy for solving the fault when the computing system fails.It can automatically quantify the quality of operation and maintenance document, fill the gap of operation and maintenance document quantitative evaluation standard, and is conducive to urging the improvement of operation and maintenance document quality, indirectly improving operation and maintenance efficiency, so as to form a virtuous circle.

The invention relates to the technical field of computer judicial practice, and discloses a litigation lawyer-oriented multi-modal case analysis intelligent generation system and method. The system automatically collects and processes multi-source materials such as audios, images, scanners and electronic documents related to cases, converts the multi-source materials into a unified text through recognition and analysis, and intelligently extracts elements such as parties, litigation requests and key facts from the unified text. The method comprises the following steps: establishing a party-legal relationship-request-fact-evidence integrated structured case model, automatically performing request right basic analysis, legal clause matching and evidence association by a system based on the model, and automatically scheduling and finishing all association analysis tasks after a user selects a document type according to a predefined intelligent mapping relationship, so as to realize automatic association analysis. Generating various litigation documents conforming to judicial practice formats and term specifications; according to the method, the whole process from multi-modal material input, intelligent analysis to standard document generation is integrally and automatically processed, so that the case handling efficiency of lawyers and the document quality are improved.

The invention discloses a document quality evaluation method and device, equipment and a storage medium, and relates to the technical field of artificial intelligence, the method comprises the following steps: obtaining a to-be-evaluated document, and determining a document type of the to-be-evaluated document; according to the document type, performing structured analysis on the to-be-evaluated document to obtain document content information; in combination with at least one preset evaluation rule, evaluating the document content information by using the quality evaluation model to obtain an evaluation result of the at least one evaluation rule; and summarizing and evaluating the evaluation results of the evaluation rules to obtain a quality evaluation result of the to-be-evaluated document. According to the method and the device, the document content information is evaluated by utilizing the quality evaluation model according to each evaluation rule, further, the evaluation results of each evaluation rule are summarized and evaluated, so that the overall quality evaluation result of the document is accurately evaluated and obtained, the content of the to-be-evaluated document can be subsequently optimized according to the quality evaluation result, and the quality of the to-be-evaluated document is improved. Therefore, the working efficiency of the subsequent test stage is improved.