204 results about "Validation rule" patented technology

The invention provides a low-code dynamic configuration method based on a natural language, and relates to the technical field of natural language processing, and the method comprises the steps: carrying out semantic analysis on a natural language description input by a user through an intelligent agent, extracting a page type, a field attribute, a verification rule and interaction logic, and generating structured configuration data; dynamically generating JSON metadata for describing page layout, field components, verification rules and interaction logic according to a preset template on the basis of the structured configuration data; according to page function requirements, interface metadata matched with the JSON metadata is generated, and the interface metadata comprises a request address, a parameter list and corresponding SQL (Structured Query Language) operation logic; and analyzing the JSON metadata by utilizing a low-code configuration rendering engine, dynamically generating an interactive management function page, and modifying the JSON metadata in real time and re-rendering the page through natural language interaction between a user and an intelligent agent.

The invention discloses a data processing method and system based on a bidding and tendering management platform. The method comprises the following steps: obtaining a bidding and tendering data set and constructing an initial supplier set; dynamically screening the initial supplier set based on a preset qualification verification rule to generate a compliance supplier set; performing multi-dimensional semantic analysis on bidding document contents in the compliance supplier set to generate a risk assessment report; and generating a recommended supplier sequence based on the risk assessment report and the bid invitation party demand information. The method has the following advantages and effects: semantic mapping and dynamic weight distribution among data are realized; based on dynamic rules and real-time data updating, response delay caused by manual intervention is reduced; through confidence scoring, a quotation rationality model and performance matching degree calculation, a quantifiable risk assessment report is generated, and subjective deviation is reduced; and the recommendation logic is dynamically adjusted in combination with the customized demand of the bid invitation party, and the intelligent level and the result credibility of the bid invitation and tendering process are improved.

The invention provides a digital asset security verification and information monitoring method and system, and the method comprises the steps: carrying out the classification of digital assets through employing a multi-dimensional classification model according to the type attributes of the digital assets, obtaining the classification labels and feature vector representations of the digital assets, and building a digital asset feature database; obtaining transaction historical data of the digital assets from the digital asset association map, discovering association rules and abnormal modes of digital asset transactions by using a time sequence mode mining technology, and forming a transaction verification rule base; according to the data structure of the algorithm adaptation layer, an intelligent data analysis and conversion technology is adopted, heterogeneous digital asset data is mapped to a unified feature space, standardized digital asset data is generated, and a digital asset feature database is formed; and performing deep verification analysis by using the digital asset feature database to obtain security attribute information of the digital assets, and performing dynamic assessment on the security level of the digital assets by using a multi-factor risk assessment model to generate the security rating of the digital assets.

The invention provides an API behavior prediction and security policy management and control method based on machine learning, and relates to the field of computer network security, and the method comprises the steps: obtaining API original data in real time, preprocessing the original data, obtaining the preprocessed original data, obtaining API dimension features in real time based on the preprocessed original data, and fusing the API dimension features to obtain unstructured data, establishing a dynamic feature validity verification rule to pre-process the unstructured data to obtain a standardized feature tensor of a unified dimension; joint modeling of API behavior spatio-temporal characteristics is carried out through a collaborative architecture of a multi-head time attention mechanism and a dynamic graph neural network, API behavior prediction is carried out, an API dynamic security management and control strategy is generated in real time through a strategy engine, strategy execution is carried out, a security strategy execution effect is monitored in real time, and iterative optimization is carried out. According to the invention, the problems that the security control strategy of the traditional API gateway is fixed and rigid, and the security strategy is difficult to dynamically adjust according to the real-time access condition and behavior are solved.

Various aspects of the disclosure relate to automated testing for application programming interfaces (APIs). A dynamic API validation computing system leverages a generative AI model to dynamically generate a multitude of data sets and rules for use during API validation activities. A federated byzantine agreement mechanism performs the validation of each API using the generated test cases and test data. A generator engine incorporates a generative AI model that may be trained on a large corpus of API metadata and / or data characteristics to predict data patterns and / or validation rules for each of the APIs under test. The generator engine may also predict a structure and format of requests based on the training model inputs. Multiple Test cases for an API created through use of the generative AI model may be distributed and executed on different testing nodes that reach a consensus about whether each API has passed or failed.

The invention provides a business rule automatic processing method and system based on natural language understanding. The method comprises the following steps: extracting text content from an original document containing business rules and preprocessing the text content; utilizing a BERT-based metadata extraction model to extract structured metadata from the preprocessed text content; confirming and perfecting the structured metadata; on the basis of the confirmed metadata, a rule execution flow chart and / or a test case are / is automatically generated and used for verifying the correctness of rule logic; and according to the target format, converting the verified rule into a corresponding symbolic representation through a template engine to obtain a defined rule. According to the invention, the automatic conversion of the business rule from the natural language description to the symbolized executable form is realized, so that business personnel can directly use the natural language to define and maintain the business rule, the manual conversion cost is reduced, and the accuracy and efficiency of rule processing are improved.

The invention discloses a permission verification method and system applied to OA examination and approval, and relates to the technical field of permission verification, and the method comprises the steps: receiving an examination and approval request triggered by an OA system, carrying out the extraction according to the examination and approval request, and obtaining user identity information and an examination and approval content label set; triggering a multi-level permission verification mechanism based on the user identity information, and generating a dynamic verification rule set; performing permission verification on the approval content label according to the dynamic verification rule set, and formulating a target verification rule; and executing the target verification rule to perform multi-level cross verification on the user permission, generating a permission verification report according to a verification result, and feeding back the permission verification report to the OA system to trigger a subsequent approval process. The technical problems of low approval process efficiency and inaccurate authority control caused by fixed static rule configuration in the authority verification process in the prior art are solved, and the technical effects of improving the authority verification flexibility and accuracy and enhancing the approval process safety and intelligent level are achieved.

The invention discloses a business filling scene data acquisition method and system, a storage medium and electronic equipment, and the method comprises the steps: firstly storing filling historical data and domain knowledge into a vector database, and according to the current input of a user, searching related information, and combining the current input to generate a filling suggestion through a generation type large model; multi-modal information of the multi-end filling system is obtained, semantic understanding and information extraction are completed through a large model, and the multi-modal information is converted into structured data; mapping the structured data to a specified field by means of a field mapping rule; a data verification rule is designed, data verification is corrected through a rule engine or large model dynamic logic verification, and a verification result and a prompt suggestion are output; and finally, storing the processed and verified data, and providing data support for the user. According to the invention, the data acquisition efficiency is improved; the intention of the user can be predicted, corresponding suggestions can be provided, and the legality and accuracy of data are ensured.

The invention belongs to the technical field of cross-data island consensus, and particularly relates to a cross-data island consensus verification method and system based on credibility scoring. According to the invention, by dynamically evaluating the trust degree of each data island and combining network state fluctuation, real-time verification and abnormal early warning of a consensus result are realized, the stability and safety of cross-data island cooperation are effectively improved, the data consistency is ensured, the data risk caused by network fluctuation is reduced, the self-adaptive capability of the system is enhanced, and the method is suitable for large-scale popularization and application. In the consensus process, historical interaction events and a current cooperation state of a data island are considered, efficient alignment of cross-island features is achieved through a gradient exchange mechanism, a standardized consensus data view is generated, in addition, self-adaptive adjustment of a consensus verification rule is ensured by pre-deploying a trusted execution environment, and the consensus verification efficiency is improved. And the consensus accuracy and efficiency are further improved.

Computer-implemented system for real-time validation and threat mitigation for structured health transactions, including: a client policy repository that contains client-specific validation rules, consent restrictions, and risk thresholds; a trusted policy execution enclave that only allows policies and models after remote attestation of code and configuration, and decrypts and processes protected fields exclusively within the enclave; a grammatically aware streaming validator that enforces format and semantic constraints and synthesizes an auto-repair suggestion in case of parser errors, transforming inputs into a policy-compliant form with minimal changes; a hybrid risk engine that calculates rule-based and learned risk scores and furthermore evaluates a subset of features using data protection-preserving calculations to determine risk contributions without decoding selected fields; a causal graph generator that correlates related transactions over time into an entity-resolved, time-aligned graph and identifies impossibility patterns with edge-wise responsibility values; a coordinator for federated learning who updates models from client-local aggregates under differential privacy budgets and suspends aggregation when a distribution drift above a policy threshold is detected; an audit subsystem that generates zero-knowledge evidence demonstrating that selected compliance predicates for a transaction have been met without disclosing protected health information; a risk-adaptive flow control system that directs high-risk substreams into micro-quarantine sections with enhanced testing while maintaining the basic service quality for low-risk substreams; and a register that stores a validity context mark which links each decision to the identity of the policies, models, scope of consent and runtime environment used.

The invention discloses a multi-terminal detection score offset correction method and system, particularly relates to the field of financial risk control, is used for solving the problem of steady-state offset generated in the merging process of multi-terminal detection scores, and comprises the following steps: receiving cross-terminal original behaviors and collecting metadata under unified time reference and unified field specifications; the method comprises the following steps: extracting a terminal fingerprint table according to a sampling beat, a sensing path, a rendering mode and a quantification strategy, generating a time alignment table, dividing a stable fragment, a change fragment and a transition fragment by taking the terminal fingerprint table and the time alignment table as conditions, and constructing a segmented order-preserving mapping relation table; a cross-terminal consistency constraint graph is generated based on the segmented order-preserving mapping relation table to form a correction rule set, rules are verified in an offline playback window, a micro-correction list is output, and the correction rule set and the micro-correction list are read in the online merging stage to execute correction and output a unified scale score. And meanwhile, generating a feedback abstract, submitting, filing and publishing a version.

The invention discloses an intelligent extraction method and equipment for structural data of a scanned copy and a medium, and relates to the cross technical field of computer vision and intelligent document processing. The method comprises the following steps: acquiring a to-be-processed scanned copy image, and performing joint feature extraction on the scanned copy image based on a preset multi-modal neural network model to generate intermediate feature representation; constructing an extensible structured index template library containing field rules, value domain constraints and cross-field verification logic; based on an attention mechanism, performing intelligent semantic matching and mapping on the intermediate feature representation and a target field in an extensible structured index template library to output preliminary structured data; based on a verification rule preset in an extensible structured index template library, executing automatic logic verification and conflict resolution on the preliminary structured data to generate standard structured data conforming to business specifications; and carrying out serialization output on the standard structured data according to a predetermined format.

Systems and methods for automatically updating validation rules used to detect and remediate network operation validation anomalies in conglomerate-application-based ecosystems are disclosed. The disclosed anomaly evaluation platform can dynamically monitor a set of document repositories containing specific guidelines for generating validation reports. In response to detecting updates in the guidelines, the anomaly evaluation platform retrieves a communication map defining parent-child relationships between validation rules and generates an updated communication map. The anomaly evaluation platform detects a transmission of a first network operation to a software application, which uses the first network operation to generate a second network operation. The anomaly evaluation platform provides the first network operation, the second network operation, and the updated communication map to an artificial intelligence model to generate a validation report that meets the specific criteria guidelines.

Systems and methods use dynamically generated validation rules. These validation rules comprise a first validation rule portion that is generated using a standardized validation process (e.g., corresponding to a standardized schema) and a second validation rule portion that is generated using a validation process selected based on a non-standardized schema that is specific to a respective asset type of the plurality of respective asset types.

A data processing system and method, and a related device, relating to the technical field of artificial intelligence (AI). The data processing system comprises a general-purpose processor and an AI accelerator card. The general-purpose processor is used for sending an operation request comprising authorization authentication information and requesting to process an AI model deployed in the AI accelerator card. The AI accelerator card is constructed to be provided with a trusted execution environment (TEE), and the AI accelerator card is used for running a policy enforcement point (PEP) component deployed in the TEE, and is further used for receiving the operation request and determining whether the authorization authentication information in the operation request complies with a verification rule in the PEP component, and when the authorization authentication information complies with the verification rule, the first operation request is executed to execute a processing operation on the AI model. In this way, the PEP component is deployed in the TEE of the AI accelerator card, that is, the PEP is deployed in an execution environment closer to the AI model, so that the AI model can be effectively prevented from being illegitimately accessed by the general-purpose processor, thereby ensuring access safety of the AI model in the AI accelerator card.

The invention belongs to the field of medical data processing. The invention provides a multi-modal data verification system and method in medical scientific research. The method comprises the following steps: extracting multi-modal data from different storage media; respectively analyzing and processing the extracted multi-modal data, respectively establishing a feature data model of each modal data and establishing a feature index; mapping the feature data models of the modal data to a unified vector space, performing data fusion according to the relationship of feature indexes of the feature data models, and generating and storing a wide model with multi-dimensional indexes; and according to a verification rule in a data processing process, slicing the wide model according to the feature index, and extracting a data feature information part corresponding to the verification rule to complete data verification. The method has the beneficial effects that all data of different modalities are subjected to homogenized fusion, so that verification for data of the same modality is not needed any more, and the verification result is more accurate.

The invention discloses an automatic verification method and system for digital data of a railway signal drawing. The method comprises the following steps: acquiring the digital data of the railway signal drawing; based on a preset verification rule, carrying out single static verification on the digital data of the railway signal drawing, finding errors and risk points, and recording and analyzing to form a static verification report; wherein the static verification comprises wiring double-end reflection conformity, relay type correctness and a static verification rule of power supply loop wire wiring ring formation. According to the method, aiming at basic data errors possibly existing in the design process of the drawing, the digital and structured drawing data are automatically checked through the preset checking rule, errors and risk points are found, and the method is an effective measure for data error correction.

The invention relates to the technical field of pollution source supervision, and discloses a pollution source off-site supervision method and system based on big data, and the method comprises the steps: building a dynamic verification rule library through coupling the operation beat data of enterprise key equipment and the total power consumption fingerprint data, and comparing the matching degree between the actual energy consumption and the expected mode in real time and generating a process credibility index. According to the invention, conversion from traditional pollution discharge data verification to production process stability verification is realized, and an unforgeable supervision trust mechanism is constructed through the physical relevance between the equipment start-stop signal and the power utilization characteristic; and meanwhile, the judgment accuracy under the extreme working condition is ensured by utilizing environmental parameter dynamic compensation and micro-differential pressure bypass verification, and finally a quantifiable accumulation enterprise environmental protection credit evaluation system is formed.

The invention provides a commodity traceability management intelligent anti-counterfeiting method and system based on the Internet of Things, and relates to the technical field of anti-counterfeiting traceability of the Internet of Things, and the method comprises the steps: carrying out the vectorization processing of commodity physical feature data, obtaining a unique feature vector, constructing a circulation link structure, and building a bidirectional binding relation; and irreversible Hash transformation is carried out in the circulation event, a node record is embedded, a tamper-proof traceability voucher is formed, and a verification rule set is constructed to carry out consistency and integrity verification. According to the invention, the commodity information can be effectively prevented from being tampered, and the reliability and anti-counterfeiting efficiency of the traceability process are improved.

Systems and methods for validations related to software. In some embodiments, a method for building software with software action validations, the method comprising: accessing a target object type, the target object type comprising one or more object properties; accessing an action type, the action type comprising one or more action parameters, the action type associating with editing a target object of the target object type; generating a set of validation rules associated with the action type, wherein the set of validation rules comprise a local validation rule associated with a rule parameter; and building a software application, wherein the software application comprises the target object type, the action type, and the set of validation rules.

The invention discloses a multi-terminal collaborative enterprise management system and method, and relates to the technical field of intelligent management, and the method comprises the following steps: dividing port data, obtaining a login verification result, executing a first operation, setting a verification rule of the port data, verifying ownership, executing a second operation, and storing encrypted data to a cloud data storage center. The enterprise data is reasonably divided into different port data, fine management of the data is facilitated, the efficiency and the safety of data processing are improved, it is ensured that only authorized users can access the system, the safety is enhanced, data leakage and unauthorized access are prevented by setting verification rules and performing ownership verification, and the safety of the system is improved. According to the method, the data cannot be read by unauthorized persons even if the data is intercepted and captured in the transmission or storage process, and users at different places and devices share and update the data in real time due to the characteristic of multi-terminal collaboration, so that the collaboration efficiency of a team is improved.

The invention provides an integrated circuit verification software development method and system supporting multiple process nodes, and relates to the technical field of integrated circuits. Receiving a target integrated circuit design file input by a user and a selected process node, extracting corresponding parameter information from the process node database according to the selected process node, and extracting a corresponding verification rule set from the verification rule base; performing parameterization processing on the target integrated circuit design file by using the extracted parameter information to generate an optimization design file containing process specific information; and executing a multi-level parallel verification process based on the optimization design file and the extracted verification rule set.

The invention provides a composite QR code verification method and system based on a coding transformation mechanism. The system comprises a code generation system, a QR code generation system and a verification server. During generation, the first code and the second code are generated, the codes are converted, the composite QR code meeting the verification rule can be generated, and the composite QR code can be verified. The composite QR code can be applied to the fields of commodity anti-counterfeiting, process management and the like so as to guarantee the authenticity of the commodity endowed with the composite QR code or the reliability of the process management process.

Systems and methods for automatically updating validation rules used to detect and remediate network operation validation anomalies in conglomerate-application-based ecosystems are disclosed. The disclosed anomaly evaluation platform can dynamically monitor a set of document repositories containing specific guidelines for generating validation reports. In response to detecting updates in the guidelines, the anomaly evaluation platform retrieves a communication map defining parent-child relationships between validation rules and generates an updated communication map. The anomaly evaluation platform detects a transmission of a first network operation to a software application, which uses the first network operation to generate a second network operation. The anomaly evaluation platform provides the first network operation, the second network operation, and the updated communication map to an artificial intelligence model to generate a validation report that meets the specific criteria guidelines.

The invention provides a composite QR code verification method and system. The system comprises a code generation system, a QR code generation system and a verification server. During generation, the composite QR code meeting the verification rule can be generated based on the generated first code and second code, and the composite QR code can be verified. The composite QR code can be applied to the fields of commodity anti-counterfeiting, process management and the like so as to guarantee the authenticity of the commodity endowed with the composite QR code or the reliability of the process management process.

Systems and methods for automatically updating validation rules used to detect and remediate network operation validation anomalies in conglomerate-application-based ecosystems are disclosed. The disclosed anomaly evaluation platform can dynamically monitor a set of document repositories containing specific guidelines for generating validation reports. In response to detecting updates in the guidelines, the anomaly evaluation platform retrieves a communication map defining parent-child relationships between validation rules and generates an updated communication map. The anomaly evaluation platform detects a transmission of a first network operation to a software application, which uses the first network operation to generate a second network operation. The anomaly evaluation platform provides the first network operation, the second network operation, and the updated communication map to an artificial intelligence model to generate a validation report that meets the specific criteria guidelines.

The present invention provides a power grid model verification method based on shape constraints, including the following steps: Step 1, convert the attribute constraints and association constraints in the classes of the power grid CIM into shape constraints on the power grid model RDF data graph; Step 2, convert the basic constraints extracted from the CIM subset and the user-defined power grid model verification rules into a power grid model SHACL shape graph; Step 3, provide the power grid model RDF data graph and the power grid model SHACL shape graph to the SHACL validator for model verification of shape constraints, and output a power grid model verification report.

The invention relates to the technical field of transaction processing process optimization, and provides a task issuing method and device, computer equipment and a readable storage medium, and the method comprises the steps: receiving a template editing instruction through a template library, and generating or modifying a task template based on the template editing instruction; in response to the task release request, calling a target task template from a template library, obtaining task basic information and approval chain information, and configuring task trigger rules including a trigger mode, a complex date rule and a precondition; according to the task triggering rule and the target task template, a task instance containing a form is automatically generated, and a task notification is generated and sent to a preset filling terminal; and when the filling terminal fills in the task form, calling a preset verification rule in the target task template in real time to verify input data corresponding to the task form so as to complete release of a task corresponding to the task form. According to the invention, a universal solution is provided for complex scenes such as financial compliance management and medical data submission.

The configuration method, device and electronic device of the business processing flow provided by the present application relate to the field of data processing technology. In the present application, the data source is configured and processed. The business processing rules of the input data are configured, and the electronic device is used to process the input data according to the business processing rules to output target output data, wherein the electronic device also outputs at least one intermediate processing data in the process of processing the input data according to the business processing rules, and the target output data is obtained by the electronic device processing the at least one intermediate processing data according to the business processing rules. The verification rules of the business processing rules are configured, and the electronic device is used to extract at least one intermediate processing data according to the verification rules to verify the business processing rules. Based on the above method, the problem of poor management and control effect of the business processing flow in the prior art can be improved.

The present disclosure relates to a method [400] and a system [300] for dynamically provisioning and configuring one or more counters at an application The present disclosure provides a transceiver unit [304] to receive a counter provisioning request, associated with a set of counters that are further associated with the application. Further, a validation unit [306] may determine a validation status associated with the counter provisioning request based on a set of predefined counter provisioning validation rules. Further, a provisioning unit [308] dynamically provisions one or more counters from the set of counters associated with the counter provisioning request based on the validation successful status. Further, the provisioning unit [308] configures the one or more counters based on the dynamic provisioning of the one or more counters in real time, at the application.