161 results about "Compliance analysis" patented technology

The invention discloses an AI generation content detection and review method, device and equipment and a storage medium, and the method comprises the steps: receiving multi-modal input data which comprises text data, image data and video data; calling a large language model to carry out compliance analysis on the text data to obtain an analysis result; when the analysis result is compliance, calling a multi-modal model to identify and detect the image data and the video data, and respectively obtaining an image detection result and a video detection result; and aggregating the analysis result, the image detection result and the video detection result to obtain a content detection result. According to the method, the processing paths are automatically allocated according to the content types, redundant calculation is avoided, hardware consumption is remarkably reduced, the multi-modal detection results are aggregated into structured output, the large-batch content processing efficiency is remarkably improved, calculation resource occupation is greatly reduced, and seamless integration of the detection results and a downstream service system is achieved.

The invention relates to the field of standard comparison analysis, in particular to a method for automatically identifying differences of domestic and overseas standard files. A method for automatically identifying differences of standard files at home and abroad comprises the following four steps of S1, standard file analysis and information extraction, S2, semantic understanding and information integration, S3, standard difference comparison, S4, compliance analysis and suggestion, and in combination with a rule engine and a natural language generation technology, evaluating difference influences and outputting adjustment suggestions. According to the method, comprehensive analysis of the standard file is realized through multi-modal integration and structured processing, and a knowledge base with cross-language and format is constructed; clause association reasoning is realized through deep semantic analysis and knowledge graph construction; according to the method, accurate difference recognition is achieved through hybrid embedding and a dynamic threshold strategy, the accuracy and efficiency of standard comparison are remarkably improved, the manual intervention cost is reduced, and an efficient solution is provided for standard system analysis in international trade and technical cooperation.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes of financial science and technology, medical treatment and health and the like, and discloses a violation content auditing method, device and equipment based on multi-modal data and a medium. Inputting the visual semantic features and the composite audio features into a multi-modal model, generating fusion features through model alignment and fusion, and analyzing the fusion features based on a knowledge base to judge whether illegal content fragments exist in the multi-modal data, and when the illegal content fragments exist, positioning the illegal content fragments in the multi-modal data and generating an auditing report. According to the method, the visual semantic features and the composite audio features are fused, cross-modal compliance analysis is realized in combination with the knowledge base, frame-level or time-axis-level positioning is performed on the illegal content segments, and the auditing report containing the evidence is generated, so that the problems of insufficient single-modal detection accuracy and poor positioning capability are solved, and the auditing accuracy is improved.

The invention relates to the technical field of financial large models, and provides an RAG method and system for compliance analysis of a multi-modal financial document, and the method comprises the steps: carrying out the preprocessing of an input multi-modal financial document, generating a corresponding text block through the multi-modal data in the multi-modal financial document, and constructing a corresponding vector database; responding to the target query request; according to the target query statement, entering a multi-path retrieval process to generate a binding packet for responding to the sub-query statements; based on the binding packages generated by the multi-path retrieval module, the semantic alignment degree of each binding package and a sub-query statement is calculated, a corresponding time reward score is calculated in combination with a time reward mechanism to obtain a matching score, ranking optimization is conducted on the matching score through a direct preference optimization mechanism, and a preference text block set is obtained to respond and generate a corresponding answer; by integrating the preprocessing module, the retrieval module and the reordering module of the financial document, the defects of the traditional method in the aspects of processing heterogeneous financial data and improving the retrieval recall rate and correlation are effectively overcome.

The invention relates to a security state evaluation method and device of a network environment, equipment and a storage medium. The method comprises the following steps: acquiring security monitoring data generated by a plurality of data sources in a network environment; the security monitoring data comprises log data, flow data and vulnerability data; extracting security features from the security monitoring data; the security features comprise statistical features, time sequence features and semantic features; inputting the security feature into a security situation model, determining security assessment index values of multiple dimensions according to the security feature through the security situation model, and determining a security situation assessment result of the network environment according to each security assessment index value; and matching the security situation assessment result with the network security compliance rule to generate a network security compliance analysis result of the network environment. By adopting the method, the security state evaluation accuracy of the network environment can be improved.

The invention relates to the technical field of operation and maintenance safety compliance, and discloses an operation and maintenance service automation safety compliance detection system and method. The system comprises an operation and maintenance event acquisition unit, a strategy execution unit, a compliance analysis unit, a strategy optimization unit and a violation tracing unit. The operation and maintenance event acquisition unit captures operation and maintenance operation events and execution environment parameters in real time, packages the operation and maintenance operation events and the execution environment parameters into event data packets and transmits the event data packets to the strategy execution unit; the strategy execution unit extracts a reference strategy rule from the security strategy library, performs matching verification on the event and generates a result; the compliance analysis unit analyzes compliance fluctuation characteristics through a multi-dimensional compliance deviation model in combination with historical records; the strategy optimization unit dynamically adjusts the event capture frequency and corrects a strategy matching rule according to the fluctuation characteristics; the violation tracing unit counts the risk cumulant and generates a violation tracing instruction when the risk cumulant exceeds a preset capacity. According to the system, automation and dynamic adjustment of operation and maintenance safety compliance detection are realized, and a risk accumulation process can be effectively tracked.

Computer-implemented systems and methods are disclosed, including systems and methods for performing compliance testing using language models or other machine learning models. A computer-implemented method may include, for example, accessing a content item; accessing a compliance ruleset; executing a compliance checker that utilizes a set of machine learning models; generating a prompt that includes the content item and the compliance ruleset; processing the prompt using the compliance checker; responsive to receiving a compliance determination dataset that indicates whether the content item satisfies one or more criteria within the compliance ruleset from the compliance checker; and generating an output based at least in part on the compliance determination dataset.

The invention belongs to the field of bill recognition, and provides a bill recognition method, system and equipment based on a large model, and the method comprises the steps: obtaining bill image data containing text information, and carrying out the preprocessing of the obtained bill image data; evaluating image quality, language distribution and layout complexity of the preprocessed image, and determining a processing path of document image data by integrating evaluation results; according to the determined processing path, calling a corresponding optical character recognition model to extract text information in the document image data; performing deep semantic analysis on the extracted text data by using a pre-trained deep learning large model, and extracting key feature information; and performing rule compliance analysis on the text information or the extracted key feature information, and generating an identification analysis report according to an analysis result. According to the invention, the processing speed and accuracy are improved, the adaptability to various document formats is enhanced, and the limitation in the prior art is effectively solved.

The embodiment of the invention discloses a method for intelligently assisting in reviewing a water conservation scheme of a water and soil conservation production and construction project, and the method achieves the intelligent feature matching of a new scheme and similar cases through the construction of a tagged knowledge base integrating historical cases of multiple industries, so as to recognize the generality compliance. A double-engine review mechanism is adopted, a form review module automatically checks document structure integrity and format specifications, and a logic review module executes cross-chapter data consistency check and business logic compliance analysis and highlights and positions error positions in a document. And recording decision logic in real time to form a feedback closed loop. And dynamically optimizing case library matching weight and recognition rules based on high-frequency error statistics and expert correction records. The modes of positioning review key points to chapters and sections, describing specific requirements of each review key point in a language, adding a check formula among data to review content needing to be calculated, determining a check type to which each review key point belongs, and the like are adopted, and the model is trained more clearly, so that the model has relatively professional review ability.

A social networking system is provided. The system encompasses a robust processing subsystem hosted on a server, comprises various modules including a registration module linking social media accounts, a blockchain-backed bio page module storing audience metrics, a payment gateway with a reward system, and a CRM module offering dashboards for influencers, brands, agencies, and followers. An analysis module integrates natural language processing to assess content tone, engagement, and sentiment. A button module generates emoticon categorization and auto-suggestions based on metadata, leveraging machine learning for predictions. A compliance analysis module ensures adherence to regulations in paid social media content, and a royalty distribution module calculates and allocates royalties based on engagement, location, compliance, and fan type via smart contracts, This comprehensive subsystem integrates functionalities to elevate user interaction, content analysis, and monetization opportunities within the social media platforms.

The invention discloses a highway engineering construction remote material abnormity management method, which relates to the technical field of material management, and comprises the following steps: collecting material information parameters for analysis, obtaining an analysis result and carrying out abnormity identification, outputting an abnormity identification result, triggering a response mechanism for the abnormity identification result, and carrying out automatic early warning. By constructing a full-process digital highway engineering construction remote material anomaly management system, the problems of multiple types of traditional management are solved, multi-source data are integrated to automatically correct errors and generate accurate data, and the material anomaly management system is established by means of space-time dimension cross validation and construction process compliance analysis. A preset abnormal feature combination library is combined to capture a composite risk, a hierarchical response and a mapping table are adopted to realize differential early warning, responsibility is clarified through receiving verification and block chain evidence storage, and a closed loop is formed by combining treatment with template optimization and dual verification, so that the risk is reduced, and the management intelligence and refinement level is improved.

The invention discloses a big data governance method and system based on a rule engine, belongs to the technical field of big data processing, and aims to solve the technical problems of low efficiency, slow response and rule stiffness in the current data governance process. Comprising a data access layer used for collecting data from each data source; the metadata management module is used for constructing a knowledge graph based on the metadata; the rule engine module is used for constructing a rule base; the data quality evaluation module is used for analyzing and evaluating the multi-source heterogeneous data based on the rule base; the authority control and compliance auditing module is used for performing authority control and performing compliance analysis on data operation through a preset compliance scale board based on an auditing log; the governance engine module is used for carrying out governance operation on the multi-source heterogeneous data based on the data quality analysis result to form a data governance execution result; and the feedback optimization module is used for optimizing the AI large model based on the data governance execution result.

The invention relates to a power grid multi-modal data compliance monitoring method based on a knowledge graph, and the method comprises the following steps: S1, obtaining multi-source heterogeneous data of a power grid, carrying out the preprocessing, and generating structured and semantic data representation; s2, constructing an initial knowledge graph according to the produced structured and semantic data representation; s3, according to the initial knowledge graph, combining a time perception mechanism TGN to identify compliance standards and laws of a power grid operation environment changing with time, combining rule-based logical reasoning with a deep neural model through neural symbol fusion, realizing compliance judgment under a fuzzy condition, and constructing a knowledge agent; s4, based on the knowledge agent, performing multi-modal compliance analysis in combination with deep learning and symbolic reasoning to obtain an analysis result; and S5, based on an analysis result, in combination with a natural language generation technology, automatically generating an interpretation report for the violation event. According to the invention, dynamic intelligent compliance analysis is realized, and the intelligent and automatic level of power grid management is significantly improved.

The invention discloses a BIM model automatic examination method and system based on visual large model image analysis and standard knowledge base coupling. The scheme comprises the following steps of training data collection and labeling, professional image review model training, review roaming path definition, profile image acquisition and processing, image compliance analysis, standard knowledge base matching, optimization suggestion generation and report output. By training an image review model in a professional field and combining with a dynamic specification knowledge base, detail problems which are difficult to find by a traditional method in a BIM model can be automatically recognized, optimization suggestions are provided by matching with real-time updated building specifications, a full-closed-loop review process from image analysis to specification verification is realized, review efficiency and accuracy are remarkably improved, and the review efficiency and accuracy are improved. And labor dependence is reduced.

The invention discloses a common data platform compliance early warning system based on legal risk indicators, which belongs to the technical field of compliance management, and specifically comprises the following steps: a request analysis module receives a data processing request containing a data subject identifier, a processing purpose and a timestamp; the feature extraction module obtains dynamic authorization features such as a historical authorization range sequence and recent change records; the compliance analysis module generates legal risk indexes based on the legal rule base; the decision fusion module generates a compliance early warning decision through multi-dimensional fusion calculation; the execution control module realizes complete release, condition limitation or complete blocking according to the decision; the traceability recording module constructs a complete decision traceability record; according to the invention, through dynamic authorization analysis, multi-level law matching and intelligent decision fusion, accurate early warning and effective management and control of the compliance risk of the public data platform are realized.

The invention discloses a fixed-wing aircraft non-airport take-off and landing adaptability evaluation method based on test flight performance data, and belongs to the field of aviation aircraft design. Comprising typical difference analysis of a non-airport environment and an airport environment, takeoff and landing sliding tolerance analysis of the unmanned aerial vehicle in the non-airport environment and takeoff and landing lateral deviation tolerance analysis of the unmanned aerial vehicle in the non-airport environment. The non-airport take-off and landing adaptive capacity of the airplane is analyzed through take-off and landing data of previous test flights. Key differences and possible problems faced by taking off and landing in the non-airport environment are found out by comparing the test flight airport environment with the non-airport environment, and key constraints of taking off and landing in the non-airport environment are formed; taking-off and landing taxiing section flight parameters in the test flight data are extracted, conformity analysis is carried out from all constraint dimensions, and the conformity analysis comprises analysis of taxiing tolerance based on grounding point deviation and analysis of taxiing feasibility of all levels of roads based on taxiing side offset distance probability distribution; whether field cleaning work needs to be carried out or not during taking-off and landing is evaluated by combining airplane height and highway guardrail design standard comparison.

The invention provides a work fund compliance auditing method and system based on a big language model, and relates to the technical field of compliance auditing, the method comprises the following steps: extracting an unstructured text, and using the big language model to carry out data cleaning, privacy desensitization and standardization processing; based on a large language model and a retrieval enhancement generation technology, constructing a work fund compliance knowledge graph, performing deep auditing analysis on standardized data, and identifying income and expenditure anomalies, asset vulnerabilities and compliance risks; building a compliance rule base by using a large language model, and performing automatic compliance judgment; generating a differentiated improvement suggestion, a rectification path and an audit report first draft, and continuously optimizing a model and a rule; the system comprises a multi-source data acquisition and preprocessing module, a deep audit analysis module, a compliance analysis module, a decision support and report generation module, and a learning and optimization module. According to the invention, through automation and intelligentization of the work fund auditing process, the auditing efficiency, the auditing accuracy and the self-adaptive capability are remarkably improved.

The invention discloses a mobile application privacy policy compliance detection method based on a big language model, and particularly relates to the field of privacy protection.The method comprises the steps that operation behaviors before and after a mobile application calls system permission are collected, a behavior path chain of a time sequence is constructed and input into a big language model with behavior intention description specialization, and the big language model is constructed; node semantic interpretations are generated and connected in series to form a behavior intention chain; and based on the change direction between the adjacent semantic segments, determining a behavior jump relationship, and constructing a system permission purpose evolution diagram. Extracting natural language paragraphs related to permission purposes in the privacy policy, and analyzing and generating a system permission purpose declaration range set; and performing semantic coverage comparison on the use nodes in the evolution diagram and the declaration range, identifying the use nodes which are not covered by the declaration, backtracking a behavior source structure based on a connection relationship in the diagram, positioning use expressions which are not covered in the privacy policy content, and outputting a structured privacy policy compliance analysis result.

Systems and methods for analyzing compliance of an online service with pre-established regulations or standards are provided herein. In one example, a method includes a step of receiving a request to perform a compliance analysis on a cloud-based service to determine whether the cloud-based service complies with multiple compliance standards applicable to an environment in which the cloud-based service is intended to operate. The method further includes a step of collecting compliance controls associated with each of the multiple compliance standards. Also, the method includes a step of automatically organizing the compliance controls to reduce the number of assessment steps. The method further includes a step of enabling implementation of one or more assessment stages using the reduced number of assessment steps to determine whether the cloud-based service complies with the multiple compliance standards.

The invention discloses an electric power monitoring credible security operation and maintenance cooperation method, system and device based on a block chain, and a storage medium, and relates to the technical field of electric power monitoring, and the method comprises the steps: obtaining sensing data of an electric power monitoring terminal side, and carrying out the signature; in combination with the operation and maintenance instruction, block chain consensus storage and verification of the data and the instruction are carried out, the data and the instruction passing verification are stored in a sensing data chain and an operation and maintenance operation chain of the block chain, and verification evidence is provided; acquiring a node historical behavior data set, and performing dynamic trust value calculation and permission allocation; performing operation and maintenance instruction compliance analysis and response in combination with a preset electric power safety regulation logic library, and generating a defense strategy set in combination with the attack feature library; the method guarantees the authenticity and integrity of data, and eliminates the forgery risk. The compliance verification time consumption is reduced from the hour level to the millisecond level, the cross-department cooperation efficiency is improved, and the single-point fault and APT attack risk is reduced; the manual auditing amount can be reduced, the accident root cause can be quickly positioned, and the tracing requirement is met.

The invention relates to a technology comparative analysis system and method based on standard semantic analysis and a computer readable recording medium. According to the system, dimension reduction processing is carried out on process data and standard texts through a semantic clustering module, and a semantic mapping relation between processes and standard terms is constructed; generating a contrast set by using a process operation standard threshold construction module and a convolutional network; and calculating a compliance score by adopting a contrast learning module. The system supports dynamic updating of a multi-dimensional standard knowledge graph, analyzes texts and recognizes semantic equivalent pairs through a natural language processing technology, achieves intelligent comparison and deviation recognition of process data and standard rules, automatically generates compliance reports and early warning information, and finally achieves digital management of enterprise standard full life cycles. And automation and accuracy of compliance analysis are improved.

The invention relates to the technical field of computer vision, and discloses a data center operation and maintenance behavior compliance analysis method and system based on a camera, and the method comprises the steps: analyzing an action feature type in an operation and maintenance operation action image, so as to determine an abnormal behavior judgment threshold value of an operation and maintenance behavior; calculating an operation and maintenance compliance score of the operation and maintenance behavior; analyzing the operation coherence and the permission mapping goodness of fit of the operation and maintenance personnel to calculate the compliance correlation degree of the operation and maintenance behaviors during compliance check; determining a compliance checking process corresponding to the operation and maintenance behavior, and analyzing a data center equipment operation period constraint in a current execution scene of the operation and maintenance behavior to calculate a compliance adaptation coefficient of the operation and maintenance behavior and equipment operation requirements in the compliance checking process; and executing compliance analysis on the operation and maintenance behaviors to obtain a compliance analysis result. According to the method, the camera-based data center operation and maintenance behavior compliance analysis accuracy can be improved.

The invention provides an advertisement compliance detection method and device based on retrieval enhancement generation, and the method comprises the steps: obtaining advertisement data, and enabling the data types of the advertisement data to comprise characters, pictures and videos; obtaining a content compliance judgment rule, and labeling and classifying the advertisement data according to the content compliance judgment rule to obtain a preliminary data set; then, performing data enhancement and expansion on the preliminary data set to obtain a training data set; a compliance detection model is constructed, and the compliance detection model comprises a multi-modal feature extraction module, a multi-modal feature fusion module and a compliance analysis module; training the compliance detection model by adopting the training data set to obtain a trained compliance detection model; and obtaining the to-be-detected advertisement data, and inputting the to-be-detected advertisement data into the trained compliance detection model to obtain a compliance judgment result corresponding to the to-be-detected advertisement data, thereby improving the accuracy of the detection result.

The invention relates to the technical field of electrical operation supervision, in particular to a power operation order compliance automatic identification system and method. The power operation ticket compliance automatic identification system comprises a data import module which is used for receiving and analyzing structured operation ticket text data and associating and importing a video file of a corresponding operation execution process; the multi-modal data processing module comprises a voice recognition unit and a video analysis unit; the compliance analysis module is used for comparing and analyzing the output results of the voice recognition unit and the video analysis unit with the operation ticket text data and judging the compliance of the operation process; and the report generation module is used for generating a structured compliance review report. Through cooperative work of the multi-modal data processing module and the compliance analysis module, automatic analysis of an operation order execution process is realized, the problems of missed judgment and misjudgment caused by subjective factors are avoided, and objectivity and fairness of an examination result are ensured.

The invention relates to the technical field of thermal power generating unit operation safety, in particular to a thermal power generating unit operator operation behavior evaluation and guidance system based on big data analysis. Comprising a multi-source operation data analysis module, an operation time sequence compliance analysis module, a dynamic operation evaluation module, an equipment state coupling analysis module and an intelligent operation guidance generation module. Wherein the multi-source operation data analysis module is used for collecting original data; the operation time sequence compliance analysis module is used for calculating and generating a time sequence compactness evaluation value reflecting the operation rhythm compliance degree and calculating an equipment aging influence compensation value; the dynamic operation evaluation module is used for outputting a comprehensive operation compliance index; according to the method, the operation behavior data and the equipment state information are fused, quantitative identification of the operation rhythm compliance and the risk level in the operation process of the thermal power generating unit is realized, and the grading guidance strategy is generated based on the evaluation result, so that the operation safety is improved.

The invention discloses a security protection method and system based on an MPLS-VPN routing network, and relates to the field of network security protection, and the method comprises the steps: firstly, obtaining PE router configuration, carrying out the static compliance analysis, and recognizing a potential configuration risk point in advance; and then, aiming at the identified risk point, scheduling a probe to carry out connectivity test, and directly verifying whether the isolation between the VPNs is broken or not. Meanwhile, in combination with flow data analysis, whether abnormal cross-VPN flow exists or not is determined. And finally, performing multi-source intelligent association on a configuration risk report, a probe connectivity result and an abnormal flow alarm, and accurately confirming a VPN flow leakage event. Through the mode, false alarm and missing alarm are avoided, so that more comprehensive and more accurate security protection of the MPLS-VPN routing network is realized.

The invention relates to the technical field of computers, and particularly discloses a security product self-evaluation report intelligent auditing method based on artificial intelligence assistance, and the method comprises the steps: analyzing a self-evaluation report to generate structured detection item data; carrying out multi-modal feature extraction and fusion on the text and image proof materials; semantic conflicts, configuration compliance, evidence credibility, image-text consistency and historical risk matching degree are analyzed in parallel through an artificial neural network, a support vector machine, a random forest, logistic regression and a weighted neighbor algorithm; according to a preset weight, dynamically fusing results of all dimensions to determine a compliance probability; similar historical cases are retrieved in combination with a security product compliance analysis knowledge graph, and auditing instructions and improvement suggestions with violation positioning bases are generated; and finally, outputting a structured auditing report and supporting continuous optimization of a manual reexamination feedback driving model. According to the method, high-precision, full-dimension and automatic security product self-evaluation report auditing can be realized, and the auditing efficiency, objectivity and large-scale processing capability are remarkably improved.

A social networking system is provided. The system encompasses a robust processing subsystem hosted on a server, comprises various modules including a registration module linking social media accounts, a blockchain-backed bio page module storing audience metrics, a payment gateway with a reward system, and a CRM module offering dashboards for influencers, brands, agencies, and followers. An analysis module integrates natural language processing to assess content tone, engagement, and sentiment. A button module generates emoticon categorization and auto-suggestions based on metadata, leveraging machine learning for predictions. A compliance analysis module ensures adherence to regulations in paid social media content, and a royalty distribution module calculates and allocates royalties based on engagement, location, compliance, and fan type via smart contracts. This comprehensive subsystem integrates functionalities to elevate user interaction, content analysis, and monetization opportunities within the social media platforms.

The invention provides an electric power production system operation compliance monitoring and early warning method. The method comprises the following steps: constructing a system library according to a system document of an electric power production system; generating a standard log document according to the operation record document and the notification record document of the power production system; the standard log document is input into the large model for key content extraction, and a structured log text is obtained; performing system searching and matching in a system library according to the structured log text to obtain a target system text; the structured log text, the target system text and contextual information are input into a large model for compliance judgment, a compliance analysis text is obtained, and the contextual information comprises historical record information of related equipment, materials and personnel related to the structured log text; and if the compliance analysis text characterizes that the operation is not compliant, triggering an early warning generation process. According to the method and the device, the limitation of the traditional method in the aspects of efficiency, accuracy, real-time performance and adaptability is effectively solved.

The invention provides a coal mine monitoring system measuring point compliance analysis method and device and electronic equipment, and the method comprises the steps: obtaining a plurality of evidence sources of measuring points in a coal mine monitoring system, and a recognition frame for the compliance analysis of the measuring points, the recognition frame comprising a plurality of candidate compliance analysis results of the measuring points; determining a basic probability distribution function of each evidence source based on the identification framework; fusing the basic probability distribution functions of the evidence sources to obtain a fused basic probability distribution function; and based on the fused basic probability distribution function, determining a target compliance analysis result of the measuring point from the identification framework. Therefore, compliance analysis can be carried out on the measuring points of the coal mine monitoring system based on the evidence theory, and multi-dimensional analysis can be accurately carried out on each measuring point. Besides, automatic measuring point compliance analysis is realized, dependence on manpower is greatly reduced, labor cost and labor intensity are remarkably reduced, and overall efficiency of coal mine safety management is improved.