40 results about "Conditional logic" patented technology

A system for improving employee engagement and automating the integration of business processes. The system includes: a user interaction module configured to receive multimodal inputs, including natural language text and voice requests from employees via enterprise portals, mobile applications, voice-activated devices, and collaboration platforms, and to generate real-time responses via conversational output channels; a context processor that is operationally coupled with the user interaction module, wherein the context processor stores the interaction history, employee preferences, organizational role metadata, and task results in both short-term and long-term memory and dynamically derives context for controlling responses and initiating workflows; A natural language and intent processor that is communicatively linked to the context processor. The intent engine consists of large language models trained on company-specific lexicons to perform intent detection, entity extraction, ambiguity resolution, and sentiment or urgency classification from employee queries; a workflow orchestration layer in communication with the intent engine and the context processor, wherein the workflow orchestration layer includes a rule-based and AI-powered process execution engine configured to automatically initiate, route, and complete cross-functional business tasks, including approvals, escalations, and compliance checks, with workflows defined using modular templates that include conditional logic and time-based triggers; Webhooks and authentication protocols provide secure interoperability between the workflow orchestration layer and external enterprise platforms; a feedback and learning module that is operationally coupled with the workflow orchestration layer and the natural language understanding engine, wherein the feedback and learning module is configured to analyze task completion rates, response accuracy, latency metrics, and user feedback signals, and to retrain underlying language and workflow models for adaptive improvement in real time; and an administration console with role-based access controls, compliance dashboards, audit trails and interfaces for workflow configuration, whereby the administration console enables authorized personnel to monitor system operations, adjust interaction rules and enforce data protection restrictions across departments.

The invention relates to the technical field of data processing, and discloses a method and a system for dynamically generating declaration receipts based on custom configuration, the method comprises the following steps: constructing a component library, the component library comprises multiple types of data item components, and each data item component is packaged into an independent module; based on the graphical configuration process, adding the components in the component library to a working area, and setting field attributes; setting a dependency relationship between fields based on conditional logic, defining a legality rule of the fields based on a data verification rule, and automatically storing a historical version in a configuration process based on version control; and based on preset authority and distribution setting, determining a filling person range and a filling time limit of the declaration receipt, and notifying a filling person. According to the invention, the form creation efficiency is improved, the maintenance cost is reduced, and the expandability and applicability of the system are enhanced.

The invention discloses a dynamic document template generation system and method based on large model workflow, and relates to the field of artificial intelligence technology, natural language processing and document automatic generation. Comprising the steps of 1, performing demand analysis on document demand description input by a user by adopting a pre-training language model and extracting document types, structural elements and business rules, 2, constructing a template structure according to an analysis result, distinguishing fixed contents and variable fields, defining conditional logic and synchronously displaying a template effect, and 3, constructing a template structure according to the analysis result. The method comprises the steps of receiving a user adjustment instruction and carrying out template optimization, 3, automatically matching variable fields with business database data, establishing dynamic association and automatically filling field contents according to the association relationship, 4, carrying out compliance detection on generated template contents and formats, prompting potential problems and enabling a user to carry out correction according to prompts. 5, according to the template confirmed by the user, the template scheme is converted into a construction instruction, and a standard format document is output; and 6, operation behaviors of the user are recorded, optimization features are extracted, the template library is updated, logic is generated, and continuous evolution of the template is achieved.

The invention provides a natural language-driven scientific research naming and ranking patient matching method and system, belongs to the technical field of artificial intelligence and medical information processing, and solves the problems of high manual workload, difficulty in semantic analysis, insufficient logical reasoning ability and the like in an existing cancer patient screening mode. The method comprises the following steps: analyzing a containing and arranging condition in a natural language text form in the tumor field to obtain a structured containing and arranging condition logic rule set; performing entity recognition, relation extraction and portrait construction on the multi-modal medical record of the cancer patient to obtain a comprehensive cancer portrait of the patient; and performing logic matching on the comprehensive cancer portrait of the patient and the structured accommodating and discharging condition rule set, determining whether the patient meets accommodating and discharging conditions, and generating a traceable matching interpretation path. The method can effectively solve the problems of large manual workload, difficulty in semantic analysis, insufficient logical reasoning ability and the like in the existing cancer patient screening mode.

The invention provides an auditing text auxiliary compiling method and system based on a large language model, and belongs to the technical field of intelligent office. Efficient reuse of experience is realized by constructing a structured knowledge base and performing word segmentation, entity recognition and theme clustering on historical documents by utilizing a natural language processing technology; dynamically generating an adaptive template, automatically filling fields in combination with service data, and supporting conditional logic to adjust contents; calling a large language model to generate a standard text, generating a table and a chart in combination with Pandas and a visual tool, and realizing multi-element mixed arrangement and format automatic verification; a user is guided to edit through an interactive interface and is stored in a knowledge base, a closed-loop evolution mechanism of auditing knowledge from reuse, generation to feedback is formed, and the normalization and efficiency of text writing are improved.

The invention relates to the technical field of data processing, and discloses a rule-based business identification method and device, equipment and a storage medium, and the method comprises the steps: obtaining the identification information of a target object, and extracting a target field associated with the object from a database based on the identification information; inputting the target field into a preset rule set, and executing matching through conditional logic to obtain a rule matching state set; determining a target rule expression according to the matching state set, and calculating the target rule expression to generate a corresponding service identifier processing result; and establishing association between the processing result and the target object to form corresponding service identification information. According to the invention, structuring, automation and high efficiency of service identifier generation can be realized, and the problems of delay and inconsistency of manual configuration are avoided; the service judgment accuracy is improved, and the flexibility and expansibility of rule processing are improved, so that the system can quickly adapt to complex and changeable service scenes.

The invention relates to the technical field of static application security detection, and discloses a training data generation method and system based on static application security detection, and the method comprises the steps: analyzing a source code of a target application program, obtaining a key condition variable and a use position, and introducing condition logic on the basis, an unsecure execution path is created that is triggered under a particular runtime condition. And then, according to the conditional logic, generating environment simulation information during operation, verifying the source code sample into which the conditional logic is introduced, determining whether a defect exists in combination with the environment simulation information, and finally generating a defect label. The method effectively solves the problem that an existing SAST tool is difficult to effectively capture the hidden security defect triggered under the specific runtime condition when facing a modern complex software system, especially a micro-service or distributed architecture application.

The invention provides an AI-based policy analysis and enterprise intelligent matching method and system, and the method comprises the steps: mapping original policy elements of a policy text to a structured rule template, and generating a policy situation model; carrying out AI identification on enterprise information of a target enterprise input by a user, and generating an enterprise standard portrait; performing field mapping on the enterprise standard portrait and the access condition of the policy situation model to determine a policy set; performing weighted calculation on the matching fields of the policy set based on the matching factor of the policy situation model, and generating a matching value of each policy in the policy set for the target enterprise; and binding the matching value with the identification information of the target enterprise to generate an enterprise policy matching result. Through implementation of the scheme of the invention, the original policy elements are mapped to the structured rule template to generate the policy situation model, the enterprise standard portrait is constructed, and in combination with access condition logic judgment, accurate matching of the structured logic model is realized, and the accuracy of enterprise policy recommendation is effectively improved.

Techniques are provided for processing rules expressed in a domain-specific language. A computing system may receive a rule including an entity identifier, a property of the entity, and one or more logical operators delimited by syntactic tokens of the language. The rule is parsed into an abstract syntax tree (AST) representation that structurally represents entities, properties, and conditional logic, and the AST is transformed into an executable function configured to evaluate input data objects defined according to a machine-readable data model. Execution of the function on input data produces a logical outcome along with intermediate results corresponding to evaluations of individual conditions and logical operators. The computing system generates an execution trace comprising the logical outcome and the intermediate results, the trace being stored in a structured log retrievable to provide evidence of how outcomes were determined.

The invention relates to the field of medical information processing, in particular to a medicine accurate query system based on artificial intelligence, and the system comprises a document analysis module which is used for analyzing the past and current diagnosis and treatment medical advice and diagnosis and treatment data of a patient to obtain a structured document analysis result; the query module is used for performing rule matching and reasoning calculation based on the analysis result to generate medication consistency test data; the scheme generation module is used for converting the inspection data into an executable drug administration plan; and the scheme correction module is used for adjusting the drug administration plan in real time based on the execution feedback data. Through medical advice clause logic analysis and medication time axis construction, time logic and conditional logic extraction is realized, and the reasonability of medical advices is ensured through conflict detection; furthermore, rule mapping is carried out in combination with changes of diagnosis and treatment monitoring indexes, a recommended medication plan is generated, dynamic correction is carried out under execution feedback, and accurate query based on reasoning can be realized under complex medical record information.

A systems and methods for determining a risk score for lookalike domains are disclosed. A plurality of candidate domains are generated from a seed domain using a genetic algorithm that applies deception techniques. Registered candidate domains are analyzed by multiple independent scoring engines that produce an internal deception score, a reputation score, a visual similarity score based on rendered webpage analysis, and a favicon similarity score. The individual scores are dynamically weighted and combined using conditional logic to calculate a final risk score. The weighting adapts based on signal strength, including prioritizing visual cloning indicators or malicious infrastructure signals. Unregistered domains are assigned reduced priority. When the final risk score exceeds a predefined threshold, an alert is generated. The disclosed approach integrates lexical, infrastructure, and content-based signals to reduce false positives and improve detection of sophisticated phishing domains.

A novel system and method for identifying and establishing personalized audio parameter settings for a person with hearing loss and / or certain listening preferences, without requiring a traditional audiogram or hearing test as a starting point. Instead, two new elements are combined: (1) A group of original sample profiles, and (2) An original tuning flow methodology and algorithm. The tuning flow methodology and algorithm includes a decision-tree conditional logic and structured series of questions that leverage a) the group of sample profiles, and b) new approaches to user interface interaction.

In some examples, a method involves rendering a graphical user interface having an Assignment Map canvas for specifying an Assignment Map, the Assignment Map graphically representing configuration data for a set of one or more user devices. User input specifies a set of conditional logic blocks at respective graphical positions within the Assignment Map canvas, each conditional logic block comprising one or more conditional logic nodes, each conditional logic node having a respective assignment rule and a respective set of Library Items. For each user device, the set of conditional logic blocks are evaluated in an order determined by a relative graphical position of each conditional logic block along a root line within the Assignment Map canvas. Each user device is then configured using respective configuration data generated based on an evaluation outcome of the plurality of conditional logic blocks.

This invention provides a method and system for assisting in the writing of audit text based on a large language model, belonging to the field of intelligent office technology. By constructing a structured knowledge base, it utilizes natural language processing technology to segment, identify entities, and cluster topics in historical documents, enabling efficient reuse of experience. It dynamically generates adaptable templates, automatically fills in fields with business data, and supports conditional logic adjustments to content. It calls the large language model to generate standardized text, and combines Pandas and visualization tools to generate tables and charts, achieving multi-element mixed layout and automated format verification. Through an interactive interface, it guides users to edit and save to the knowledge base, forming a closed-loop evolution mechanism for audit knowledge from reuse and generation to feedback, improving the standardization and efficiency of text writing.

The invention discloses a construction waste language guidance segmentation system and method fused with invalid instruction recognition, and belongs to the technical field of artificial intelligence. According to the method, after cross-modal information is extracted and a semantic memory token is output, parallel segmentation and verification are executed in a second Swin Transform Stage, a third Swin Transform Stage and a fourth Swin Transform Stage of a Swin Transform visual coding network based on the semantic memory token and a negative memory token, candidate segmentation masks and existence probability scores are obtained, decision output is carried out through a gating mechanism with a preset confidence threshold, and the candidate segmentation masks and the existence probability scores are obtained. The output instruction is valid and invalid; and finally, after conditional logic modification is executed, joint loss is calculated, back propagation and optimization are carried out, and model training is carried out, so that the robust language guide segmentation system and method for invalid instruction interference are realized. The key problem that invalid instructions cannot be recognized and rejected during construction waste sorting is innovatively solved; and a powerful technical guarantee is provided for realizing real, reliable and efficient intelligent sorting of the construction waste.

The invention discloses a mathematical application question synthesis method based on a hierarchical entity network. And constructing a hierarchical entity network. A plurality of entities are generated using a hierarchical entity network. And forming a corresponding tree structure according to the entities generated by the hierarchical entity network. Selecting known entities, questioned entities and redundant entities from all the entities; in the tree structure, an answer path points to the questioned entity node from the known entity node; and generating a problem solving step in a mathematical calculation form according to the entity arithmetic operation relationship and / or the numerical arithmetic operation relationship among the nodes passed by the answer path. A mathematical application question described in a natural language is generated according to the format of background stories-known conditions-logical relations-questioned entities; and a big language model is adopted to describe the problem solving steps in a mathematical calculation form into answers in a thinking chain form by adopting a natural language. According to the method, mathematical application questions with diversity and complex logicality are generated based on algorithm design of a hierarchical entity network.

A system includes a controller configured to reconstruct a continuous waveform into a discrete analog version. The system includes a numerical optimizer configured to determine the frequency of a pulse sequence. The numerical optimizer uses radial motion mode frequencies and desired gate times. The numerical optimizer generates the pulse sequence by disabling phase space trajectories, unwrapping spins and motion, and limiting the Rabi frequencies of motion sideband transitions. The system also includes a display configured to illustrate the discrete-frequency modulated pulse sequence based on the determined frequencies.

The present application relates to a kind of rule-based aerospace equipment system level simulation guiding and adjusting intervention system and method, the system includes: scenario loading subsystem, for the structured data in external scenario file is parsed, form the initialization data required for guiding and adjusting rule editing and situation display;Guiding and adjusting rule editing subsystem, for the definition, generation and sending of the rule of guiding and adjusting intervention;Situation display subsystem, for the detailed parameter display of guiding and adjusting result in guiding and adjusting intervention process Visual display;Rule guiding and adjusting model, for the condition satisfaction of simulation scene according to conditional logic monitoring, and according to the condition satisfaction Guiding and adjusting instruction set is sent.The present application solves the problem that traditional guiding and adjusting is easy to appear missed judgment, delay, timeliness is not strong, complex rule support is not strong, realizes the full process automation, can guarantee the adaptability of system simulation complex guiding and adjusting rule, can also guarantee the accuracy and real-time performance of guiding and adjusting intervention process execution.

A document review system that displays a workflow builder interface comprising a block library and a workflow canvas. The system receives user selection of workflow blocks including rule execution blocks, conditional logic blocks, and output blocks, enables positioning of the blocks on the canvas, and receives user-defined connections between blocks. The system receives natural language rule definitions through prompt fields and document selections through context selectors, processes the rule definitions using an artificial intelligence engine to generate executable operations, receives conditional expressions for workflow branching logic, configures output parameters, and executes workflows defined by the positioned blocks and connections.

This invention provides a method and storage medium for multi-dimensional feature fusion and dimensionality reduction of transmission line data, involving data processing technology. The method standardizes the multi-dimensional impact data to obtain standard data; determines the feature structure as a two-dimensional feature, uses the standard data as the first data, counts the first frequency of each sub-category in the first data, and performs nonlinear weighted fusion processing on the first frequency to obtain a first fusion value; when the feature type is determined to be multi-dimensional, uses the standard data as the second data, classifies the second data based on preset conditional logic, counts the second frequency of each risk level, and performs nonlinear weighted fusion processing based on the risk level and the second frequency to obtain a second fusion value; based on the first fusion value and the second fusion value, obtains the risk value of the monitoring target, identifies abnormal targets based on the risk value, and determines the maintenance route map of the UAV based on the target area of ​​the abnormal target.

Methods and systems for managing service deployment are disclosed. To deploy services, dependencies and other characteristics (such as context data, capability data, placement rules, and workflow data) of services and the infrastructure boundaries in which the services are running may be dynamically collected, analyzed and updated. By dynamically analyzing dependencies and other characteristics (such as context data, capability data, placement rules, and workflow data) of services and the infrastructure boundaries, efficiency of use of computing resources may be improved by recycling existing workflow; statically defined operations and hard-coded conditional logic of services may also be avoided each time an environment in which the services are running has changed.

The application discloses a query condition conversion method and device for adaptive AI output correction, and relates to the technical field of artificial intelligence and natural language processing. The method comprises the following steps: receiving a user natural language input, dynamically constructing a system prompt word based on target table field metadata, sending the system prompt word to a large language model together with the user natural language input, obtaining a JSON format query condition array and transmitting and storing the JSON format query condition array. JSON strings in the array are extracted and converted into a query condition object array, logical operator position correction processing is performed on the query condition object array, the first query condition logical relationship is set to be empty, and the logical operator value of the previous query condition is read as the logical relationship of the previous query condition. The corrected array is converted into a system internal data structure, a database query is performed by using the system internal data structure, and data records meeting the conditions are obtained and returned. The problem that a large language model sets a logical operator on a previous expression, resulting in incorrect query results, is solved.

The application relates to the technical field of static application security detection, and discloses a training data generation method and system based on static application security detection, which obtains key condition variables and usage positions by analyzing the source code of a target application program, introduces condition logic on the basis, creates an unsafe execution path triggered under specific runtime conditions, generates runtime environment simulation information according to the condition logic, verifies the source code sample after the introduction of the condition logic, confirms whether defects exist in combination with the environment simulation information, and finally generates a defect label. The method effectively solves the problem that existing SAST tools are difficult to effectively capture hidden security defects triggered under specific runtime conditions when facing modern complex software systems, especially microservice or distributed architecture applications.

The application discloses a visual AI auxiliary writing and intelligent diagnosis system and method for quantification strategy learning, and belongs to the technical field of financial technology and artificial intelligence. The system comprises: a teaching AI strategy generation module, which analyzes natural language strategy description into a three-layer structure of a strategy skeleton layer, a condition logic layer and a parameter configuration layer, generates a structured strategy description language intermediate representation with three-layer teaching annotations of logic annotations, variant prompts and learning point annotations, and converts the structured strategy description language intermediate representation into target real-time environment code; a learning path adaptive scheduling module, which adopts deep reinforcement learning dynamic planning personalized learning paths based on user multi-dimensional capability portraits and strategy difficulty quantification models; a strategy risk diagnosis and market adaptation module, which generates a strategy multi-dimensional risk portrait, calculates strategy-market adaptation degree scores and triggers early warnings; a strategy variant intelligent generation module, which generates diversified strategy variants based on a genetic algorithm and analyzes parameter-performance influence modes through comparative learning; and a multi-agent collaborative strategy diagnosis module, which performs parallel diagnosis by four special agents of code auditing, overfitting detection, market sensitivity analysis and signal quality evaluation, performs causal reasoning by an arbitration agent, and generates a natural language diagnosis report. The application solves the problems of poor code learnability, incompatible learning and real-time code, lack of personalized path guidance and intelligent diagnosis tools in existing quantification strategy learning platforms, and significantly reduces the learning threshold of quantification strategies.

Provided are computing systems and methods designed to enable bulk document generation while creating immutable logic records. A document generation system receives a bulk document request, wherein the bulk document request comprises request metadata. The system accesses one or more document templates, wherein at least one of the one or more document templates include conditional content. The system filters the one or more document templates based on the request metadata. The system generates a plurality of documents based on the one or more document templates, wherein each document in the plurality of documents is intended for delivery to a particular document recipient in one or more document recipients. The system transmits the plurality of documents to one or more document recipients.

A branch predictor predicts a first outcome for a first branch in a first block of instructions. Fetch logic fetches instructions for speculative execution along a first path indicated by the first outcome. In response to taking the first predicted outcome, information representing a remainder of the first block is stored. In response to not taking the first branch instruction, the branch predictor is restarted based on the remainder block. In some cases, an address of the first block is used as an index into a branch prediction structure to access an entry corresponding to a second block along a speculative path from the first block. A corresponding set of instances of branch condition logic are used to simultaneously predict outcomes for branch instructions in the second block, and in response to a misprediction, the predicted outcomes are used in combination with the remainder block to restart the branch predictor.

The present disclosure provides a data query method and device, equipment and storage medium, and relates to the technical field of databases. In some embodiments of the present disclosure, by setting a filtering input rule, ambiguity in filtering logic condition analysis can be avoided as much as possible under the premise that the filtering logic has sufficient degrees of freedom; by setting a mapping parameter table, the target distributed large table can be quickly located according to the field, and scanning all large tables can be avoided; the query relationship between the table and the filtering condition is determined through the filtering condition logic analysis rule, and combined with the statement generation rule, a query template that does not need to be associated is finally formed. Assuming that the distribution fields of all distributed large tables are one of the query target fields, or one of the fields is the primary key, the query template does not need to perform data transmission before data query, thereby saving computing resources and improving query efficiency.

Systems and methods for automatically performing actions for a user or system in response to receiving natural language statements. The systems and methods use a large language model to transform the natural language statements into conditional logic for domain specific systems, which systems can perform the corresponding actions. In domains such as a data center or a smart city, the systems and methods provide an intelligent system that can identify conditional statements including conditions and corresponding actions in response to natural language statements. These conditional statements are interpreted as rules in the context of the domain, such that the methods and system ascertain that conditions are met and perform corresponding actions. If there are issues interpreting the conditionals, the systems and methods can use a feedback loop to gather additional information.

The invention discloses a query condition conversion method and device for adaptive AI output correction, and relates to the technical field of the crossing field of artificial intelligence and natural language processing. The method comprises the steps of receiving natural language input of a user, dynamically constructing system cue words based on target table field metadata, sending the system cue words and the natural language of the user to a large language model, obtaining a JSON format query condition array, and transmitting and storing the JSON format query condition array. JSON character strings in the array are extracted and converted into a query condition object array, logic operator position correction processing is carried out on the query condition object array, the logic relation of the first query condition is set to be null, and the previous logic operator value is read as the logic relation with the previous query condition according to the subsequent query condition. And converting the corrected array into a system internal data structure, executing database query by using the system internal data structure, and obtaining and returning data records meeting conditions. The problem that a query result is wrong due to the fact that a logic operator is arranged on a previous expression by a large language model is solved.

The invention discloses a vehicle configuration cloud collaborative management method, device and equipment and a storage medium, and relates to the technical field of Internet of Vehicles, and the vehicle configuration cloud collaborative management method comprises the steps: embedding dynamic configuration parameterization logic to carry out parameterization definition on a template, the dynamic configuration parameterization logic comprises configuration item placeholders, variables, expressions and conditional logic; receiving vehicle state context information of the target vehicle and a configuration type of the request; selecting an applicable target template based on the vehicle state context information and the configuration type of the request; and analyzing and executing expressions and conditional logic in the target template, dynamically filling configuration item placeholders, and generating a configuration data set of the target vehicle. According to the method, the configuration value can be automatically rendered through the vehicle state context information and the requested configuration type, so that the configuration can be dynamically generated as required.