58results about How to "Improve review efficiency" patented technology

The invention discloses an automatic auditing system and method for road engineering completion settlement. The system comprises a data acquisition and integration module; a data preprocessing module; a settlement index construction module; an intelligent auditing engine; an abnormity early warning and tracing module; a settlement result management module; and a data analysis and optimization module. The auditing method comprises the following steps: S1, collecting and integrating multi-source settlement data; s2, big data preprocessing; s3, constructing a settlement auditing index system; s4, performing intelligent automatic auditing; s5, performing abnormal early warning and tracing; s6, managing settlement results; and S7, performing big data driving optimization. According to the invention, multi-source data intelligent integration, full-process automatic auditing, abnormal accurate tracing and dynamically optimized big data driven settlement auditing can be realized; the method is applied to whole-process management of road engineering completion settlement, and data-driven intelligent auditing and continuous optimization control are realized in the process.

The invention discloses a man-machine collaborative auditing and optimizing method for AI (artificial intelligence) generated content oriented to the field of literature and blog. The man-machine collaborative auditing and optimizing method comprises the following steps: S1, content acquisition and personalized constraint preprocessing: acquiring literature and blog field related content generated by an AI model; if the content is customized by a specific object, inputting an exclusive digital resource library and a style guide of the corresponding object into an AI generation model as constraint conditions; s2, multi-dimensional automatic evaluation: calling a multi-dimensional content evaluation model to carry out automatic analysis on the content, and outputting a quality score vector containing a plurality of evaluation dimension scores; s3, man-machine task dynamic allocation and collaborative auditing: calculating the comprehensive confidence of the content based on the quality score vector, and dynamically allocating the low-confidence content to the matched artificial auditor according to the confidence and the professional portrait of the auditor; and an auditor can trigger traceability verification based on the authoritative literature and blog mapping knowledge domain during auditing. According to the method, the AI generation content in the literature and blog field can be better audited and optimized.

The invention provides a large model content generation auditing method and system based on man-machine collaboration, and relates to the technical field of large models, and the method comprises the steps: deconstructing the generation process data of to-be-audited content, constructing a content risk propagation map, mapping a multi-level auditing strategy library, and recognizing an uncertainty region needing manual intervention. And obtaining manual auditing judgment and correction operation, forming auditing knowledge precipitation and perfecting an auditing strategy library. According to the method, the content risk source can be accurately positioned, the auditing efficiency is improved, a closed-loop optimized man-machine collaborative auditing mechanism is formed, the misjudgment rate is effectively reduced, and the large model content security is improved.

The invention discloses a data auditing method and device based on artificial intelligence, electronic equipment and a storage medium, relates to the technical field of artificial intelligence, can be specifically applied to the financial and medical fields, and meets high requirements of financial and medical industries on compliance and auditing tracking while improving auditing efficiency and reducing labor investment. The method comprises the steps that in response to a data auditing request, target data to be audited are preprocessed, and a hierarchical tree structure used for describing text content and layout position information of the target data is obtained; based on the large language model, generating a field extraction cue word matched with the data type of the target data, guiding the large language model to perform field extraction on the hierarchical tree structure by utilizing the field extraction cue word, and obtaining a field extraction result output by the large language model; and performing abnormal field auditing and abnormal field evidence labeling on the field extraction result by utilizing a pre-constructed knowledge graph to obtain an auditing result of the target data, and outputting the auditing result.

The invention provides a chemical reaction diagram examination method, device and equipment, and the method comprises the steps: carrying out the information extraction of a chemical reaction diagram, and obtaining the information of a plurality of semantic units in the chemical reaction diagram; determining an association relationship among the multiple pieces of semantic unit information; according to the semantic unit information and the association relationship, the chemical reaction diagram is examined, so that the examination accuracy and efficiency of the chemical reaction diagram can be improved.

The application relates to a multi-level review and shelving management system, method and medium for an intelligent agent, and relates to the technical field of intelligent agent review management. The multi-level review and shelving management system comprises a state conversion module, a double review module, an analysis and shelving module, a traceability management module and a permission verification module. The state conversion module is used for detecting an intelligent agent according to a preset node state machine model, verifying a state conversion path of the intelligent agent and determining a state of the intelligent agent. The double review module is used for verifying stage state elements of the intelligent agent according to a state review rule in combination with the state of the intelligent agent, and constructing an intelligent agent review work order. The analysis and shelving module is used for quantifying the intelligent agent that has been shelved according to a multi-dimensional risk assessment mechanism in combination with the intelligent agent review work order, calculating a comprehensive risk score and determining a shelving type. Through a seven-state node state machine model, a double review mechanism, a forced shelving identification technology and an audit dimension quantitative scoring algorithm, accurate management and safety control of the intelligent agent in the whole life cycle are realized.

This invention discloses a molecular genetics laboratory management system for a genetics center, belonging to the field of laboratory information management technology. It provides real-time monitoring of sample status, dynamic scheduling of subsequent tasks, and early warnings for near-expiration and overdue samples. Experimental data is collected through structured electronic task sheets, and the analyzed genetic variation information is dynamically updated to a mutation database. Historical variation data is intelligently recommended for report generation. Report content is automatically populated based on variation data and adapted to project templates. It supports configurable multi-level review processes, enabling online collaboration and operation tracking. Based on review results, first-use acceptance and automatic deduction of inventory for reagents and consumables are performed. Based on resource linkage and traceability, gene disease databases and mutation databases are collaboratively constructed. This system achieves fully automated management from intelligent sample monitoring and scheduling to automatic report generation and review, significantly improving the operational efficiency, data accuracy, and resource utilization of the genetics laboratory.

The invention provides a long text-oriented analysis checking method, device and equipment and a storage medium. The checking efficiency and accuracy are remarkably improved through intelligent fragmentation and mixed scheduling. The core of the method is that according to semantic relevance among text fragments, fragments with reference or dependency are distributed to serial auditing nodes for deep and coherent context verification, independent fragments are distributed to parallel auditing nodes for concurrent processing, and therefore the problem of long text semantic segmentation is solved, and meanwhile the content of the text fragments is improved. And the auditing time is greatly shortened from the hour level to the minute level. Besides, the output behavior of the large language model is restrained by loading a predefined structured instruction set in the auditing node, so that'illusion 'and misjudgment generated when the model processes complex tables and nested terms are effectively inhibited, and the reliability of a checking result is remarkably improved. The method has flexibility and expandability, and is suitable for automatic and intelligent checking scenes of various professional long texts such as contracts and bid invitation files.

The application provides a method and system for checking the cross-modal information consistency of a maintenance plan based on a large model, and relates to the technical field of big data analysis. The method comprises the following steps: identifying a target maintenance plan through a power large model, determining key maintenance content, an unstructured proportion, and an attachment type complexity; obtaining a text data complexity and a business risk index based on key maintenance content analysis, as a first checking difficulty coefficient and a second checking difficulty coefficient; determining a third checking difficulty coefficient according to the unstructured proportion and the attachment type complexity evaluation; taking the expected review time limit of the target maintenance plan as a constraint, formulating an adaptive checking depth and an adaptive checking breadth based on the first checking difficulty coefficient, the second checking difficulty coefficient, and the third checking difficulty coefficient; and performing cross-modal information consistency checking on the target maintenance plan according to the adaptive checking depth and the adaptive checking breadth. The dynamic allocation of resources for checking the cross-modal information consistency of a maintenance plan is achieved.

The invention discloses a video auditing method and device, a storage medium, a program product and computer equipment. The method comprises the following steps: acquiring a to-be-audited video; determining a maximum frame number based on auditing demand information and the to-be-audited video; acquiring key frames from the to-be-audited video at least based on the maximum frame number and the to-be-audited video; and determining an auditing result of the to-be-audited video at least based on the key frame, so that the maximum frame number matched with the actual auditing demand can be dynamically determined according to the auditing demand information and the to-be-audited video, and the key frame is acquired from the to-be-audited video according to the maximum frame number for video auditing. Therefore, the video auditing can be efficiently completed to improve the video auditing efficiency.

The present disclosure provides a content review method, device, equipment and medium, the method comprises: determining the first document type of the to-be-reviewed document, and performing paragraph segmentation processing on the text content of the to-be-reviewed document according to the first document type to obtain a plurality of first text blocks; the first text block is subjected to vectorization processing to obtain a first vector, and the retrieval result of the first vector in the vector database is determined, the retrieval result includes: at least one candidate vector, and the similarity score of each candidate vector and the first vector; obtain the context information of the first vector in the to-be-reviewed document, and determine the content matching value between each candidate vector and the context information; determine the target vector from the plurality of candidate vectors according to the similarity score and the content matching value; determine the paragraph semantic similarity according to the first vector and the target vector; determine the content review result according to the paragraph semantic similarity corresponding to each first vector. Therefore, the content review efficiency and accuracy can be effectively improved.

This invention relates to the field of bid document management technology, and in particular to an automatic bid document review method and system based on natural language processing. The method includes: identifying target sections; determining historical performance and financial information; judging whether false performance exists; analyzing the complete sentences containing target keywords; calculating material scores; determining price deviation; and determining the review result. This invention achieves multi-dimensional and comprehensive review of bid documents by intelligently analyzing multiple sections such as qualifications, risks, materials, and pricing. This effectively improves the comprehensiveness and depth of the review. Utilizing natural language processing technology, it can accurately identify and extract key information from bid documents, overcoming the subjectivity and limitations of traditional manual review. Quantitative assessment based on risk level significantly improves the accuracy and relevance of risk identification. By comprehensively weighing material scores and price deviation, it significantly improves review efficiency.

The invention discloses a ship design drawing protocol system and method, and the system comprises a multi-specialty coordination confirmation module which supports the online coordination of multi-specialty departments, automatically detects the conflicts between specialties, and carries out the collision detection and visual marking through a 3D modeling tool; the shipboard and classification society auditing module is used for encrypting an outgoing drawing and supporting online annotation of auditing suggestions; and the version management and endorsement module is used for recording multiple rounds of confirmation versions and modification records, carrying out version comparison and difference analysis, and generating a DocuWorks drawing with electronic endorsement as an operation basis. The ship drawing review efficiency is improved, and drawing version management is enhanced.

The invention discloses a multi-agent-driven paper intelligent review method and system, belongs to the technical field of artificial intelligence, and is used for solving the technical problems that the existing paper intelligent review technology is lack of deep design for construction of expert agents, single in review dimension, insufficient in review comprehensiveness and difficult to meet the actual demand of paper intelligent review. The method comprises the following steps: constructing an examination point list based on a basic examination dimension of paper quality examination; constructing a large review model according to the historical papers and expert review data; constructing a review expert agent group based on the review expert background information and the review large model; based on the review expert agent group, the review point list and the review rule, constructing an intelligent review workflow; and inputting the to-be-reviewed papers into the intelligent review workflow to match a plurality of appropriate review expert agents in the review expert agent group to perform intelligent review on the to-be-reviewed papers to obtain an intelligent review result.

The application relates to a content review method and device, computer equipment, a storage medium and a computer program product, and relates to the technical field of artificial intelligence. The method comprises the following steps: obtaining a first reader tag set obtained by pre-launching target content in a to-be-reviewed launch area; matching the first reader tag set with a reference reader tag set corresponding to the target content to obtain a matching result; in the case that the matching result meets a preset related condition, determining that the target content meets the review condition of the to-be-reviewed launch area, and pre-launching the target content into a launch area corresponding to a next level of the to-be-reviewed launch area; taking the launch area corresponding to the next level as the to-be-reviewed launch area, returning to the step of obtaining the first reader tag set obtained by pre-launching the target content in the to-be-reviewed launch area, and continuing until the level of the to-be-reviewed launch area reaches a target level. The method can improve the content review efficiency.

The invention discloses a financial reimbursement intelligent auditing system and method based on a large model, and relates to the technical field of informatization. Comprising the following steps: step 1, obtaining audit data through a front-end interface: obtaining an attachment to be audited carrying a bill number, form information and a flow name; 2, extracting attachment information; 3, matching an auditing rule and executing the steps of presetting the auditing rule which covers invoice types, invoice expiration, invoice details and information whether attachment uploading is complete or not; matching preset auditing rules according to the cost items, performing auditing one by one according to the form information and the attachment information, and checking whether the reimbursement receipts meet various rule requirements or not; and 4, generating and storing an auditing report: after the auditing is completed, pushing the business document for manual reauditing, automatically generating the auditing report, the report content comprising problems found in the auditing process, specific conditions conforming to or not conforming to the rules, and translated Chinese file link information, and the auditing result of each rule is displayed in the form of a table.

The present application relates to a kind of structure inference, automatic analysis and standardized output of multi-variant BOM table, belong to electronic manufacturing data processing, table analysis and structured data cleaning field.The present application constructs a set of analysis architecture for multi-variant BOM table by the modular processing link of "title row detection-column head normalization-multi-column identification-variant reconstruction-segment cleaning-intelligent inheritance-standardized output", robustly locates complex table head by strong and weak evidence weighting and verification under-probing mechanism, realizes the split and identification of multiple quantity columns using stop mark and semi-finished product number analysis, and introduces cross-row backfilling and position number inheritance rules under paragraph constraint, effectively solves the analysis problem caused by template difference, multi-column variant and information loss, realizes the automation, precision and standardization of BOM data from messy input to engineering level standardized output, significantly reduces manual intervention and improves data quality.

The invention provides a ternary collaborative multi-agent framework and an environmental assessment report intelligent auditing method, and belongs to the technical field of artificial intelligence and environmental assessment, the framework comprises a decision-making layer, an arbitration layer and an evolution layer, the decision-making layer performs parallel auditing with a dynamic weight revenue function through four agents, and the arbitration layer quantifies decision conflicts with OODA circulation based on conflict intensity, and performs review on the decision-making layer and the dynamic weight revenue function through the four agents. And the evolution layer adopts a DPO method with preference attenuation to realize model iteration. And the auditing efficiency and precision are obviously improved.

The invention discloses a report review method and device, electronic equipment and a storage medium. The report review method comprises the steps that a to-be-reviewed report is obtained, the to-be-reviewed report is analyzed, structured information of the to-be-reviewed report is obtained, and the structured information comprises at least one of a structured text and structured data; identifying a to-be-reviewed participant in the structured text, identifying first associated information of the to-be-reviewed participant based on a pre-constructed knowledge graph, and performing risk review processing on the first associated information based on a risk assessment review rule to obtain a first review result; and / or identifying a to-be-reviewed data item entity of the structured data, identifying second associated information of the to-be-reviewed data item entity based on a pre-constructed knowledge graph, and performing rationality review on the second associated information based on a data rationality review rule to obtain a second review result; and generating the review report based on the first review result and / or the second review result, thereby realizing automatic review of the report.

The invention discloses a file verification method, system and device, a readable storage medium and a processor. The method comprises the following steps: in response to a file verification instruction, obtaining a to-be-verified file indicated by the file verification instruction; key text information in the to-be-verified file is extracted, and the key text information is used for representing text content in the to-be-verified file; the key text information is used for conducting format conversion on the to-be-verified file to obtain a target file, the file format of the target file is a plain text format, and the plain text format is different from the initial file format of the to-be-verified file; checking operation is executed on the target file, a checking result is obtained, and the checking result is used for representing the integrity degree of the text content in the target file. The technical problem of low document verification efficiency is solved.

This invention discloses a full-angle recognition device for a verification platform, comprising a part for collecting expiration date and batch number information and a part for collecting drug appearance information features. The part for collecting expiration date and batch number information includes one grayscale machine vision camera, one set of infrared photoelectric triggers, and five strip auxiliary light sources. The part for collecting drug appearance information features includes one color machine vision camera, two auxiliary light strips, a warning light strip, and a transparent drug verification platform. This invention employs a combination of color and grayscale machine vision cameras, assisted by light sources, to achieve effective image acquisition of drugs and rapid matching of multi-point information. It can simultaneously and quickly complete the verification of drug type, expiration date, and batch number. Furthermore, the high-performance processor significantly improves the device's operating speed and ensures its reliability.

The invention discloses a bidding and tendering file analysis method and device based on a large language model, equipment and a medium, and relates to the field of artificial intelligence. The target file comprises a bidding file and a bidding file; performing semantic segmentation on the target file to convert the target file into structured chapter segment information; uploading the chapter segment information to a target knowledge base for vectorization storage, and establishing a chapter segment association relationship between chapter segments of the bidding document and chapter segments of the bidding document; extracting target bid invitation information corresponding to the bid invitation file from the target knowledge base by using a preset large language model, and constructing a bid invitation file information base according to the target bid invitation information; and analyzing the bidding document according to the bidding document information base, the bidding document chapter segments and the chapter segment association relationship among the bidding document chapter segments to obtain an analysis result, and determining a review report based on the analysis result. According to the invention, the efficiency, accuracy and compliance of bidding and tendering review are improved.

The application relates to a processing method and system for improving recognition processing efficiency based on automatic grouping of key points, and belongs to the technical field of content recognition processing. The method comprises the following steps: receiving a processing instruction proposed by a user, analyzing all files contained in the processing instruction to obtain an examination key point list and a corresponding grouping thought chain; inputting all examination key points in the examination key point list and the corresponding grouping thought chain into a preset grouping intelligent agent, classifying all examination key points through the grouping intelligent agent to form a plurality of first examination groups; distributing an examination model to each first examination group through an asynchronous calling framework, generating and starting a plurality of examination threads, and the examination threads correspond to the first examination groups one by one, so as to process all examination key points contained in the corresponding first examination group; and obtaining and merging the examination results of all examination threads to output the results for the user to know. The application has the effect of improving the processing efficiency of multiple files.

The application provides a kind of multi-modal sensitive label identification method and system for short video content security, anchors short video sensitive representation subject and disassembles to form multidimensional fine-grained representation unit, excavates the content association logic chain between multidimensional fine-grained representation unit, obtains relevant set;Perform cross-dimension feature interlacing and link fusion processing to construct sensitive association feature network;Sensitive association feature network is matched with preset sensitive label item set to generate initial anchoring association relationship;Then, the initial anchoring set is executed feature network reverse tracing and label anchoring counteracting calibration processing, and the anchoring association deviation is corrected;Based on the calibrated label feature node anchoring set, extract sensitive label and execute label interrelation aggregation and hierarchical division processing, output the sensitive label set corresponding to short video.The application comprehensively utilizes short video multi-modal information, and improves the accuracy of sensitive label identification.

The application provides a long text review optimization method, device, electronic equipment, storage medium and program product, and relates to the technical field of text processing. The method comprises the following steps: performing semantic segmentation on a long text to be reviewed, and establishing a mapping relationship between semantic segments and a preset review directory; performing line number identification on the long text to be reviewed, and establishing an associated database of original text segments and line numbers; performing slicing processing on the long text to be reviewed, and generating a plurality of text slices; according to the mapping relationship, filtering out text segments related to a review task from the plurality of text slices; instructing a large model to review the text segments according to the review task, obtaining a review result and a target line number associated with the review result; according to the target line number associated with the review result, recalling a corresponding target original text segment from the associated database of original text segments and line numbers, and merging the review result and the target original text segment to generate a review report. The application improves the review efficiency and the original text recall accuracy.

The application provides a kind of intelligent examination data processing method, by receiving the target enterprise's workstation template map configured by management end, workstation template map includes multiple identification areas, identification area has corresponding examination end;Receive the examination data uploaded by each examination end, based on the examination data, the corresponding identification area in the workstation template map is handled, and the theoretical examination map is obtained;Obtain the workstation image collected by acquisition device, based on examination identification strategy and workstation template map, the workstation image is identified, and the update data of the examination end is obtained, and based on update data, the actual examination map is updated to the corresponding identification area;Based on video frame selection strategy, multiple workstation images in a predetermined time period are selected and processed, and the examination backtracking video of each examination end is obtained, and the actual examination map and the examination backtracking video are sent to the management end.

The invention relates to the technical field of environmental assessment text processing, and discloses an intelligent auditing system for an environmental assessment report based on dynamic classification and knowledge mapping, which enables a classification system to automatically identify a novel pollution type and dynamically adjust a type boundary through multi-source data fusion and an incremental learning algorithm. The method ensures that the classification result always meets the newest environmental policy requirement, and ensures that the knowledge base can synchronize the newest standard specification content in real time by establishing a classification system and a trigger updating mechanism of the standard specification, thereby achieving the effect of comprehensively improving the professionalism and timeliness of the environmental assessment system. The system can automatically adapt to environmental policy changes and technical standard updating, can maintain scientificity of a classification system and integrity of a knowledge base without manual intervention, ensures that newest and most relevant standard specifications can be called for professional judgment when various environmental assessment reports are audited, and remarkably reduces audit deviation caused by knowledge lag.

This application relates to a case file review method, apparatus, computer equipment, computer-readable storage medium, and computer program product. The method is executed by a review model and includes: acquiring a case file to be reviewed; extracting case file keywords from the case file; determining the review type of the case file based on the case file keywords; searching for review prompt words corresponding to the case file in a prompt word rule base according to the review type and case file keywords, and combining the review prompt words corresponding to the case file to be reviewed to obtain a review prompt word chain; and reviewing the content in the case file to be reviewed sequentially according to the review prompt word chain to obtain a review result. This method enables efficient and accurate case file review.

This application discloses a screen image detection method, electronic device, and storage medium. The method includes: acquiring a screen image of a screen to be detected; inputting the screen image into a preset detection network for position detection, and outputting at least one detection box; extracting a screen image to be detected from each detection box; inputting each screen image to be detected into a preset classification network, performing integrity detection on each screen image through a first classification head of the classification network, outputting a first classification result, and performing power-on status detection on each screen image through a second classification head of the classification network, outputting a second classification result; determining the detection result of the screen image based on the first and second classification results of each screen image to be detected, or filtering multiple screen images to be detected based on the first classification result and the corresponding second classification result to obtain a target screen image. The embodiments of this application achieve the filtering of high-quality screen images, improving the quality and efficiency of review.