1418 results about "Report generation" patented technology

The invention discloses a semantic enhancement auxiliary inquiry system and method based on a medical knowledge graph, and the system comprises a patient information receiving module, a theoretical knowledge graph storage library, an evidence-based knowledge graph storage library, a double-track diagnosis path construction module, a medical knowledge conflict judgment module, and a semantic enhancement report generation module. The double-track diagnosis path construction module inquires the received patient information in a theoretical knowledge graph storage library and an evidence-based knowledge graph storage library which are independent from each other in parallel, and a theoretical diagnosis path and an evidence-based diagnosis path are generated respectively; the medical knowledge conflict judgment module dynamically compares the two paths in real-time interaction, and performs priority judgment according to a preset medical judgment rule; finally, the semantic enhancement report generation module presents the two paths and the conflict judgment result to the user at the same time. Transparency and interpretability of the whole interrogation process are assisted, and reliable semantic enhancement decision support is provided for doctors when the doctors face complex medical knowledge conflicts.

The invention discloses a network security situation awareness and analysis platform based on AI, and relates to the technical field of network security situation awareness and analysis, and the platform comprises a multi-source data collection module which integrates flow, logs, assets and threat intelligence data, and carries out encryption transmission and standardization; the data preprocessing module purifies and optimizes data, and guarantees data quality and sensitive information security; the AI situation awareness analysis module extracts features through a deep learning model, dynamically evaluates the situation and identifies threats; the threat early warning and decision-making module triggers graded early warning and generates a targeted emergency response scheme; the visual display and interaction module displays information in multiple dimensions and supports query and report generation; and the data storage and tracing module adopts a mixed storage architecture, so that the data security and traceability are ensured. The platform integrates multi-source data and realizes situation accurate perception and intelligent decision by means of an AI technology; the early warning is accurate, the visual interaction is convenient, and the intelligent and efficient level of network security protection is comprehensively improved.

The invention relates to the technical field of database security, and discloses an MCP and agent-based heterogeneous database security access and report generation method, which comprises the following steps of: receiving a task request, acquiring a task context, synchronizing capability declarations from a plurality of database adapters according to the MCP, generating a capability graph and determining a capability version identifier; performing semantic mapping to obtain a strategy inline rewriting rule and a rewriting abstract fingerprint; the method comprises the following steps: signing and issuing a minimum permission access token, generating cross-source query, performing forced rewriting according to a strategy inline rewriting rule in a compilation stage, verifying consistency, processing an original result to obtain a purified result, only allowing to read a generated report from a buffer area of the purified result under the constraint of a structured mode template, and calculating a report fingerprint at the same time. And writing a chained audit log, fixing the audit log, and verifying report reproduction based on the audit log. According to the method and the system, minimum access, unauthorized prevention and control, compliance audibility and result reproducibility are realized.

The invention relates to the technical field of data analysis, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a multi-agent traceable analysis method, device, equipment and medium, and the method comprises the steps: receiving a target theme and a data source list, collecting a multi-source document, and carrying out the preprocessing of the multi-source document to generate a preprocessing document set; configuring an analysis agent based on a semantic clustering result, and setting an analysis direction to form an analysis agent set; generating a structured note and index data table, and executing cross-document comparison to form an analysis output set; and receiving a feedback instruction to adjust the analysis agent set, triggering incremental processing to update the analysis output set, generating a theme research and judgment report, and keeping mapping consistency. According to the method, the multi-source document is fused through semantic clustering and a multi-agent cooperation mechanism, semantic association and traceable analysis are achieved, agent configuration is optimized in combination with interactive feedback, and the accuracy and the intelligent level of report generation are improved.

The invention relates to the technical field of natural language processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a document interpretation and report generation method, device, equipment and medium, which comprises the following steps: receiving an original document set to generate a structured document object, executing optical character recognition on an image content set to generate a recognition text set, the recognition text set and the text content set are combined into a unified text sequence, element item extraction is executed based on the interpretation template parameter set to generate an interpretation element set, a retrieval enhancement context is retrieved and generated from the domain knowledge base, and the unified text sequence, the interpretation template parameter set and the retrieval enhancement context are input into a language model to generate an interpretation result. And generating report content based on the historical report template set. According to the method, automatic closed loop of document interpretation and report generation is realized through multi-modal unified processing and semantic enhanced reasoning, the efficiency is improved, and the manual dependence and compliance risk are reduced.

The invention relates to a field information analysis method and system based on RAG and a knowledge graph, and belongs to the technical field of artificial intelligence, and the system comprises a multi-source heterogeneous data collection module which is used for collecting field-related original data; the intelligent document processing engine is used for carrying out cleaning and structured processing on the data and extracting entities, relationships and events; the multi-source knowledge graph construction and management module is used for constructing and fusing multi-sub-field knowledge graphs to form a unified knowledge graph; the RAG retrieval enhancement generation dynamic fusion sequencing module is used for receiving user query, performing multi-channel information retrieval by querying a text vector index and a knowledge graph, performing fusion resequencing on a result, and generating an analysis result by utilizing a large language model; and the agent workflow engine is used for decomposing query into subtasks and scheduling professional agents to cooperatively complete analysis and report generation. Deep semantic understanding, intelligent retrieval and automatic analysis of domain information are realized, and the accuracy and efficiency of information processing are improved.

The invention provides a transformer area line loss intelligent algorithm decision-making method based on a knowledge graph and a large model agent, semantic retrieval in the algorithm calling process is supported, dominant and implicit knowledge such as expert experience, technical standards and historical cases is coded in a unified mode, a mapping relation is established between algorithm nodes and process nodes in the knowledge graph, and the algorithm is optimized. An integrated reasoning path is formed, so that the intelligent agent can automatically combine and call an algorithm according to a task target, a large model is embedded into a transformer area line loss analysis process, and a hierarchical structure of'task analysis intelligent agent-algorithm decision intelligent agent-result analysis intelligent agent 'is formed; the task analysis agent is responsible for converting a problem input by a user into a structured task; the algorithm decision agent is responsible for algorithm selection and adaptive parameter adjustment; the result analysis agent is responsible for report generation and decision recommendation based on the knowledge base; according to the method, organized association can be carried out on scattered algorithm tools, expert experience and business rules, and a unified transformer area line loss agent tool integration framework is constructed.

The invention provides an official document auditing method, device and equipment based on a large model and a medium, and the method comprises the following steps: preprocessing an official document to realize format and language standardization; using a retrieval enhancement generation (RAG) technology to complete vectorization conversion and fragmentation processing; then grammar and semantic analysis is carried out through a text analysis module fused with the large model, and matching detection is carried out according to a preset rule base in combination with an automatic rule engine module; then, deep auditing is conducted by means of a machine learning auditing model, content problems are recognized, manual rechecking is triggered in case of high uncertainty or key content, and an auxiliary tool is provided; receiving an audit opinion optimization model and a rule base; and finally outputting a result, and feeding back the problem by generating a report without annotation. The document auditing efficiency and accuracy can be improved, continuous optimization is supported, and the method is suitable for multiple scenes.

The invention discloses a large language model auxiliary optimization strategic decision-making system and a large language model auxiliary optimization strategic decision-making method. The system comprises six core modules. The dynamic knowledge fusion module constructs a three-layer distributed knowledge network, constructs an entity association weight matrix through a bidirectional Transform model based on an attention mechanism, and realizes knowledge dynamic association in combination with a time attenuation factor and a hybrid coding technology. The large language model module performs field fine tuning by adopting incremental pre-training and low-rank adaptation technologies, and introduces an exclusive word segmentation list to improve professional analysis precision. The full-process intelligent writing module covers submodules for report generation, revision and the like, and supports full-life-cycle management of reports. The strategic decision intelligent deduction module integrates scene impact factors, and realizes multi-scene deduction through reinforcement learning and Monte Carlo tree search. The interaction display module provides a visual interface, and the multi-mode interaction module realizes full task chain management. According to the invention, real-time knowledge support and intelligent deduction capability are provided for strategic decision making, and decision making efficiency and accuracy are improved.

The invention discloses an intelligent traceability system for veterinary drug safety information, which relates to the technical field of veterinary drug safety and information and comprises a data fusion module, a risk traceability module, an event reconstruction module, a chain integration module, a critical path module and a report generation module. The system dynamically constructs a risk association map by fusing multi-source heterogeneous data in production circulation, actively recognizes a potential risk veterinary drug batch cluster and realizes full-chain reverse tracing. Fine-grained event reconstruction is carried out on each link, a risk event chain is formed after integration, a core event sequence causing risks is extracted by calculating the contribution degree weight of each event, and finally a traceability report and a disposal suggestion are generated in combination with a safety knowledge base. According to the system, intelligent tracing from passive query to active early warning and from link enumeration to root cause accurate positioning is realized.

The invention relates to code verification, in particular to a code and document consistency reasoning verification system based on a cross-modal logic atlas, which comprises an input layer for receiving source codes and software documents; the feature extraction layer is used for performing feature extraction on the source code and the software document; the abstraction layer is used for converting the extracted features into comparable intermediate representations; the unified modeling layer is used for mapping code logic and document semantics into a unified atlas structure and performing formalized representation by using description logic to obtain a cross-modal logic atlas; the reasoning verification layer is used for performing reasoning verification on the consistency of the code and the document according to the cross-modal logic graph; the result processing layer is used for judging a verification result according to the reasoning verification condition, starting a contradiction positioning mechanism when inconsistency is found, and carrying out contradiction positioning and report generation to obtain an interpretable report; according to the technical scheme provided by the invention, the defects that the consistency between the code and the document is difficult to accurately verify, and accurate contradiction positioning and an interpretable report are difficult to provide can be effectively overcome.

The invention discloses a document review method based on multi-agent collaboration and retrieval enhancement generation. The method comprises the following steps: firstly, analyzing a document review rule input by a user into a rule semantic intermediate representation through a natural language processing technology, and calling a retrieval enhancement generation (RAG) module to expand related knowledge to form a structured rule library; secondly, multi-modal analysis and chapter segmentation are carried out on a to-be-examined document, and elements such as texts, tables, pictures and formulas are expressed in a unified mode; tasks such as rule analysis, document segmentation, knowledge retrieval, matching comparison and report generation are completed through a multi-agent cooperation mechanism; finally, when ambiguity exists in rule and document matching, an RAG module is introduced to retrieve supplementary evidences from an external knowledge base, explanatory comparison is conducted in combination with the generative model, and the accuracy and authority of judgment are improved.

The invention discloses a property operation report generation method and device based on multiple agents and a related medium, and the method comprises the steps: calling an intention recognition agent to carry out intention analysis, and then calling a task planning agent to carry out path construction and scheme solving; determining an execution sequence of tasks in combination with the task planning data to obtain task processing data; calling a data collection agent to carry out data collection on the task processing data to obtain primary processing data; and calling a code calculation agent to carry out code generation and model operation on the primary processing data, calling an outline making agent to carry out outline arrangement and report generation processing, calling a report writing agent to complete report packaging, and outputting a property operation report. According to the invention, the structured analysis result obtained through calculation is subjected to outline arrangement and report generation processing, and the property operation report is packaged and output, so that manual report arrangement is not needed, the process is simplified, and the report output efficiency is improved.

The invention provides a 10kV cable accessory manufacturing quality inspection report generation method and system, and relates to the technical field of power equipment quality detection and reliability evidence storage. According to the method, original detection data is acquired and structured in multiple dimensions, and data sources, operators and equipment identifiers are bound, so that context integrity and traceability are realized; initial and enhanced data fingerprints are generated through block classification, standardization and Hash operation, and a dynamic fingerprint chain is constructed by using a chain structure, so that whole-course data has content and process dual integrity identifiers; a multi-level verification sequence is embedded in each stage of report generation, finally, a block chain is utilized to record a data packet abstract, an anchor point on the chain is bound with report metadata, a transaction ID is embedded into a report document, and a checking two-dimensional code is generated. According to the method, the non-tampering performance and the verifiability of the content and the generation process of the detection report and the traceability of the whole circulation process are improved.

The invention relates to the field of artificial intelligence and data analysis, in particular to a report data automatic analysis report generation system based on an AI agent. Comprising a multi-modal intention understanding and dialogue analysis module; a dynamic domain knowledge graph construction and reasoning module; the self-adaptive narrative generation and visualization module is used for dynamically generating a report structure according to an analysis result and providing an interpretable insight and a personalized report style; and the agent arrangement and self-learning closed-loop module is used for decomposing the user intention into sub-tasks, scheduling specialized micro-agents to cooperatively complete the sub-tasks, and optimizing an analysis strategy and updating a knowledge graph based on user feedback. Through multi-modal interaction and conversational analysis, a user does not need to learn a complex query language, and can naturally explore data like a conversation with human experts, so that the analysis process is more intuitive and more efficient.

A system and method includes connecting an interface device to a port of a vehicle to be in communication with an electrical system of the vehicle for monitoring the vehicle, and running a selected one of multiple available calibration and / or repair programs via the interface device to generate a calibration / repair data file of the vehicle, where the data / log file is generated in one of a plurality of possible native file formats. A report generation tool acquires screen captures and / or screen recordings to document the data / information displayed during the steps of a calibration / repair procedure. An evaluation tool extracts calibration / repair data from the data / log file, where the evaluation tool is configured to extract calibration / repair diagnostic data from data / log files in each of the plurality of possible native file formats, and outputs the calibration / repair diagnostic data to a database in a common format from which detailed calibration / repair diagnostic reports are generated.

The invention relates to the technical field of team cooperation, and discloses a team cooperation priority adjustment method based on a situation, and the method comprises the following core steps: collecting task attribute parameters, member state parameters and environment interference parameters in real time, and generating task initial priority data and situation influence weight data; the task initial priority data and the situation influence weight data are fused for conflict detection analysis, task conflict feature data are output, when the task conflict feature data exceed a preset threshold value, dynamic priority sequence data are generated, and a risk prediction model is constructed based on historical cooperation data; and performing cooperation risk prediction processing in combination with the dynamic priority sequence data, generating team cooperation risk early warning data, integrating the dynamic priority sequence data and the team cooperation risk early warning data to perform decision report generation processing, and outputting team cooperation optimization guidance report data. The task execution deviation is reduced, and the overall efficiency, stability and risk response capability of team cooperation are improved.

The present invention discloses a computer-implemented system and method for automated evaluation of Environmental, Social, and Governance (ESG) disclosures and detection of greenwashing. The system integrates artificial intelligence and machine learning techniques to extract, segment, and analyze ESG content from structured and unstructured sources. A retrieval and segmentation module identifies ESG-relevant sections, which are then vectorized and stored for semantic search. A semantic retrieval module fetches contextually relevant content, which is evaluated against predefined benchmarks using an analysis and validation module. The scoring module assigns ESG scores based on rule-based criteria including key strengths, specificity, and supporting evidence. A report generation module creates structured ESG reports with visual analytics, while an orchestrator module dynamically coordinates all processing steps based on ESG framework requirements.

The invention relates to the field of intelligent report generation, in particular to an intelligent insight report generation method and system based on an AI large model, and the method comprises the steps: inputting an insight demand, and generating an insight data package comprising insight contents, associated data and industry labels; extracting a basic keyword set of the insight data packet to form a mixed feature code; after mixed feature coding preprocessing, weight distribution is carried out; and after weight distribution of the AI large model, injecting a high-weight feature vector into a semantic understanding core layer, injecting a low-weight feature vector into a logical reasoning layer, and outputting analysis data to form an intelligent insight report. According to the method, word embedding parameters are optimized according to field semantic characteristics, a parameter verification mechanism is introduced, field text characteristics are adapted by adjusting vector dimensions, context windows and low-frequency vocabulary filtering threshold values, window parameter validity is verified through cosine similarity, word frequency threshold value reasonability is verified through standard deviation, and field text characteristic matching is achieved. And it is ensured that the feature vectors can accurately capture domain-specific semantics.

The invention discloses an API (Application Program Interface) monitoring security audit model based on a government affair system, which relates to the technical field of network security, and comprises the following steps: collecting and converging network traffic of each collection point; analyzing the distribution condition of APIs in the collected flow, identifying and displaying key information, meanwhile, realizing data real-time processing, data stream splitting, data reading and writing and offline data analysis, and detecting risk behaviors by utilizing a rule strategy library; aPI asset weaknesses are identified and marked, state management is supported, and an attacker portrait, security study and judgment and attack traceability model is constructed; and pushing and displaying risk model early warning, realizing multi-dimensional data source real-time association analysis based on a big data framework, automatically converging alarms to form an event file, and linking with automatic arrangement to complete event response and report generation. According to the method, the problem of insufficient security and stability of the government affair system is solved, and complex attacks and advanced persistent threats can be identified more accurately.

System, method, and various embodiments for a functional code generation system leveraging LLM capabilities, are described herein. An embodiment operates by receiving a user instruction to generate a report. An information prompt is generated, and an large language model (LLM) derives a plurality of vectors from the instruction, including a first vector. A first question is identified based on comparing the first vector to a plurality of questions; the first question is associated with a first query template. A query result from a collection database based on executing a query corresponding to the first query template against the collection database. The LLM is instructed to generate an answer comprising a natural language interpretation of the query result in view of the first question. The LLM is instructed to generate a report based on the answer in view of the user instruction.

The invention belongs to the technical field of shipping big data application, and particularly relates to a shipping research report generation method based on multi-agent cooperation, and the method comprises the steps: enabling a multi-agent hierarchical cooperation architecture, dividing a whole agent into a plurality of sub-agents with independent functions, and dividing the sub-agents into a management layer and an execution layer; the management layer comprises a project manager agent, an architect agent and a demand side agent; the execution layer comprises a shipping intention recognition agent, a background investigation agent, a content team agent, a review verification agent and a report writing agent; the intelligent agents cooperate with one another, and a shipping research report is written in a popular, easy-to-understand, organized and clear language according to the structure and style of the shipping report. According to the method provided by the invention, human information processing, decision making and operation processes are simulated, a modularized and multi-agent cooperative agent scheme is constructed, and the application of AI in the shipping field is pushed to a new height of comprehensive knowledge creation from operation assistance and single analysis.

The invention relates to the technical field of dangerous cargo management, in particular to an intelligent compliance verification system for dangerous cargo boxing operation. Comprising a data acquisition preprocessing unit; the law and regulation graph construction iteration unit is used for extracting a'law and regulation term number-verification dimension-constraint condition 'triple of the law and regulation in the dangerous cargo boxing field and introducing an improved three-dimensional dynamic weight conflict resolution algorithm according to the efficacy level, the release subject and the application range indexing; a multi-agent collaborative verification unit; a risk early warning report generation unit; and a man-machine cooperation closed loop unit. According to the method, the problems of lagging of laws and regulations and clause conflicts are solved by adopting triple extraction of'laws and regulations clause numbers-verification dimensions-constraint conditions', a three-dimensional dynamic weight conflict resolution algorithm based on laws and regulations effectiveness-scene matching degree-release time and a technical means of periodically optimizing weight parameters through a reinforcement learning model.

The invention discloses an inspection report generation method and device, equipment and a storage medium. The method comprises the following steps: determining abnormal inspection data and a report object of data center equipment; determining structured inspection data according to the abnormal inspection data, a preset equipment knowledge graph and a historical case library; determining a report constraint condition according to the report object and a preset report generation rule; and inputting the structured inspection data and the report constraint condition into a pre-trained large language model, and generating an inspection report oriented to the report object. According to the technical scheme, the preset equipment knowledge graph and the historical case library are constructed in advance, the fault linkage effect and the historical similar cases across the equipment are identified based on the inspection data, the inspection reports facing different report objects are dynamically generated, and the generation efficiency, the flexibility and the comprehensiveness of the inspection reports are improved.

The invention discloses a question and answer-based report generation method and device and a storage medium, and the method comprises the steps: obtaining question information inputted by a user, calling an intelligent answer model to answer the question information, and obtaining answer information; based on an answer layout style associated with the question information, performing visual rendering on the answer information to obtain an initial answer rendering result; receiving an editing operation executed by the user for the initial answer rendering result, and modifying the initial answer rendering result based on the editing operation to obtain a target answer rendering result; and in response to a report generation operation executed by the user, based on the report layout style associated with each piece of question information, performing combination and visual rendering on the target answer rendering result corresponding to each piece of question information to obtain a report file. According to the method, it can be ensured that the finally generated report file conforms to user expectation, the layout reasonability and data accuracy of the report file are improved, and the report generation efficiency is improved.

The invention relates to a fusion prediction and interpretable report generation system for multi-modal medical data, and the system comprises a data access and preprocessing module which is used for processing at least two kinds of heterogeneous modal data from a target object; the modal feature encoding module comprises a plurality of encoders corresponding to modal types and is used for extracting feature representation of each modal data; the outcome prediction module is used for outputting an outcome prediction result of each mode; the missing modal fusion module is used for dynamically adjusting a fusion weight based on a modal existence vector when at least one modal data is missing so as to realize robust prediction; and the multi-agent interpretation module comprises a plurality of interpretation sub-modules corresponding to the modals and a language model convergence device, and is used for generating an interpretable natural language report based on the multi-modal evidence. According to the method, the problems that an existing prediction technology is unavailable under the condition of lack of modals, the fusion capability is insufficient and clinical interpretability is lacked are solved, and a stable and interpretable auxiliary decision-making tool is provided.

The invention relates to the field of intelligent diagnosis of industrial equipment, in particular to an equipment fault diagnosis system and method based on a knowledge base and a large model. The system comprises a data acquisition module used for acquiring running state data in real time; the domain knowledge base is used for primarily judging the preprocessed operation state data and outputting a primary judgment result; the large model diagnosis module is used for reasoning based on the primary judgment result and the preprocessed operation state data and outputting an accurate judgment result; the accurate judgment result comprises an accurate judgment fault type, confidence and an accurate judgment basis; the report generation module is used for obtaining a diagnosis result based on the primary judgment result and the accurate judgment result, and generating and outputting a diagnosis report based on the diagnosis result; the operation and maintenance terminal is used for operation and maintenance personnel to check the diagnosis report, confirm the diagnosis result and output diagnosis result confirmation information; and the feedback updating module is used for updating the domain knowledge base and / or finely adjusting the large model diagnosis module according to the diagnosis result confirmation information.

The present disclosure provides techniques for red teaming with artificial intelligence (AI) models. A processing device generates, via a first AI model, an agent action space based on security data, where the agent action space is indicative of actions to perform to potentially compromise at least one of a computing system, a network, or an application. The processing device performs a reinforcement learning process with an agent based on the agent action space to obtain a log of the reinforcement learning process. The processing device generates, via a second AI model, a report based on the security data and at least a portion of the log, where the report is indicative of a security weakness of the at least one of the computing system, the network, or the application.

The invention discloses a dynamic active learning and knowledge graph agent-based airworthiness document review method, which comprises the following steps of: collecting and processing a multi-modal heterogeneous data source to obtain a standardized knowledge base; based on the standardized knowledge base, constructing an aviation domain knowledge system by using dynamic active learning and a man-machine cooperation mechanism; constructing a knowledge graph and performing knowledge enhancement; and dynamically constructing a review context based on a retrieval enhancement generation method in combination with the knowledge graph, and injecting an intelligent agent to perform intelligent data review and report generation. According to the method, automatic review of airworthiness documents is realized through a dynamic active learning-agent review method, and the manual review efficiency is remarkably improved; domain knowledge is injected into an intelligent agent by utilizing an RAG technology, so that the accuracy of a general large language model in an airworthiness review task is improved; through knowledge semantic driving and human-in-the-loop knowledge enhancement, the problem of scarcity of high-quality data in the field is relieved; models of different parameter scales are cooperatively utilized, and computing power resources are saved.

The invention discloses a rehabilitation medical assessment management system based on dynamic multi-scale adaptation and automatic calculation, and particularly relates to the technical field of medical assessment management. The assessment management system comprises a patient information acquisition module, a dynamic scale adaptation module, an automatic data acquisition and calculation module, a data analysis and report generation module, a rehabilitation management module and a database storage center, and the patient information acquisition module is used for acquiring patient information and storing the acquired information in the database storage center. According to the rehabilitation medical assessment management system based on dynamic multi-scale adaptation and automatic calculation, through dynamic multi-scale adaptation, the most suitable assessment scale combination can be selected according to individual differences and rehabilitation stages of patients, the rehabilitation conditions of the patients are comprehensively and accurately reflected, and the accuracy of assessment results is improved.