103 results about "Rule sets" patented technology

The system described herein can automatically match, link, or otherwise associate electronic activities with one or more record objects. For an electronic activity that is eligible or qualifies to be matched with one or more record objects, the system can identify one or more set of rules or rule sets. Using the rule sets, the system can identify candidate record objects. The system can then rank the identified candidate record objects to select one or more record objects with which to associate the electronic activity. The system can then store an association between the electronic activity and the selected one or more record objects.

A gaming system includes a processor and a memory storing a plurality of stage game rule sets. Each rule set of the stage game rule sets corresponding with a stage of a game. The processor is programmed to cause display of columns each including symbol positions based on a first game configuration for a first instance of a first stage of the game and determine a first game outcome for the first instance based on the first game configuration and a first rule set. The processor is further programmed to change the first game configuration to a second game configuration based on a first trigger symbol occurring in the first game outcome and determine a second game outcome for a first game instance of a second stage of the game based on the second game configuration and a second rule set associated with the second stage.

The specification provides a risk control strategy optimization method, an electronic device and a program product. The risk control strategy optimization method comprises: obtaining a to-be-optimized risk control strategy data set; wherein the to-be-optimized risk control strategy data set comprises a to-be-optimized risk control strategy composed of a plurality of to-be-optimized risk control rules, strategy evaluation index data and rule evaluation index data calculated under a preset risk control evaluation dimension; obtaining an optimization target for constraining the risk control evaluation dimension and a candidate rule set; the candidate rule set comprises a plurality of candidate risk control rules and rule evaluation index data calculated under the risk control evaluation dimension; based on the to-be-optimized risk control strategy data set, the optimization target and the candidate rule set, a strategy optimization prompt word is constructed; the strategy optimization prompt word is input into a language model to instruct the language model to optimize in the direction of achieving the optimization target, to reconstruct the to-be-optimized risk control strategy by referring to the candidate rule set, and to output an optimized risk control strategy and a corresponding optimization reason.

The embodiment of the specification provides a reinforcement learning method and device for a large language model. The method comprises: acquiring a base large language model with a thinking chain generation capability; driving the base large language model to generate a plurality of candidate replies for a target query statement, each candidate reply comprising thinking chain content and an answer; matching the thinking chain content in each candidate reply with a preset rule set in an artificial knowledge base, so as to determine the compliance degree of the thinking chain content with the rule set as a first reward value; determining a second reward value corresponding to the answer in the candidate reply; determining a comprehensive reward value of the candidate reply according to the first reward value and the second reward value; and updating parameters of the base large language model according to the comprehensive reward values corresponding to the plurality of candidate replies respectively. The thinking process of the model can be constrained, and the convergence speed of the model is improved.

This invention relates to the field of data management technology, specifically to a method, apparatus, computer equipment, and storage medium for multi-source data consistency management. The method includes: acquiring data records from at least two source systems to generate change events; converting the change events into evidence records containing original values ​​and contextual information based on a semantic rule registration library, and generating a standardized value view; performing entity parsing based on the standardized value view to obtain a set of candidate entity matching relationships, and outputting a credible candidate set through semantic equivalence transformation stability testing and evidence conflict measurement; performing constraint consistency inference based on the credible candidate set and the semantic rule registration library to generate a consistency state snapshot and a correction action plan; generating a synchronous execution rule set based on the correction action plan and performing a pre-rehearsal acceptance test; executing correction and re-collecting verification when successful, and rolling back when unsuccessful. This invention improves the traceability of cross-source consistency determination and the verifiability of correction execution, and reduces the risk of erroneous corrections.

The application relates to the field of natural language processing and decision intelligence, and particularly relates to a large language model reasoning method based on time series difference learning and rule enhancement, which is widely applied to automatic planning, intelligent question answering, embodied intelligence and the like. The method comprises task trajectory sampling, domain knowledge induction, domain rule extraction and large language model reasoning based on rule enhancement. For test task data, the most relevant historical task is matched based on vector retrieval, and a domain rule set corresponding to the task is obtained. The rule is rewritten in natural language by the large language model itself, so that the rule is more interpretable and adaptable. Finally, the optimized rule set is integrated into the large language model reasoning prompt text, so as to optimize the reasoning quality and stability.

This invention discloses a PCFG password strength evaluation method incorporating Pinyin patterns. The steps include: 1) extracting Pinyin patterns from a benchmark dataset and generating corresponding rule sets; 2) sequentially selecting rules from the rule set according to probability and generating corresponding passwords based on the probability of the terminal symbols in the patterns contained in the rules; 3) determining whether the currently generated password matches the corresponding user's password. If not, proceeding to step 2) changing the terminal symbols corresponding to the pattern and generating the password again. If all terminal symbols in the patterns contained in the rule have been exhausted, changing the rule and continuing to generate passwords; 4) when the password matches the corresponding user's password, determining the password strength of the corresponding user's password based on the number of rule changes. This invention significantly improves the effectiveness of password strength evaluation for passwords containing Pinyin, providing a more scientific evaluation method for user password security.

This information processing device: acquires corporate enterprise designation information that designates a first corporate enterprise to which leader information, which pertains to a substantive leader, is to be provided; acquires corporate enterprise information having beneficiary-related information that includes at least beneficiary information representing a beneficiary of the subject corporate enterprise and ownership ratio information representing the ratio at which the beneficiary owns stocks of the subject corporate enterprise; refers to the acquired corporate enterprise information and specifies the beneficial ownership rate according to a definition in an assumed designated nation; specifies a beneficiary who is the substantive beneficiary in the first corporate enterprise, on the basis of the acquired corporate enterprise information and the specified beneficial ownership rate; and extracts at least some of the beneficiary-related information corresponding to the specified beneficiary as leader information. The device further comprises a rule-set storage unit storing a plurality of rule-sets each defining a complete algorithmic logic for specifying the beneficiary according to a respective jurisdictional definition, a jurisdictional routing unit for selecting rule-sets for execution, a multi-result publication unit for comparative output of specification results from multiple rule-sets, and a scoring unit for calculating descriptive and qualitative scores characterizing the complexity and structural aspects of each beneficiary specification process.

A computer-implemented method for regulating delivery frequency of outbound communications. The method includes receiving message context data comprising one or more of a user identifier, a client identifier, a campaign identifier, a channel identifier, a label identifier, and a trigger identifier. A counter-field identifier is determined that encodes the channel identifier, label identifier, trigger identifier, campaign identifier, and a temporal-interval indicator. A counter field identified by the counter-field identifier is created. A value stored in the counter field is incremented through an atomic operation. The value is compared with a limit stored in a rule set. An allow signal is output when the value does not exceed the limit and a suppress signal is output when the value exceeds the limit. An engagement-counter record is updated to the in-memory database.

This application provides a pre-verification method and a computing device, applied to a computing device. The method includes: obtaining a verification request; the verification request is used to verify whether a first scenario has the preconditions for executing a business process; determining the first configuration information corresponding to the first scenario in a rule set configuration file based on the scenario identifier of the first scenario in the verification request; the rule set configuration file includes multiple scenario identifiers and configuration information corresponding to each scenario identifier; the first configuration information is used to indicate verification rules, data resource information on which the verification rules depend, and a result display template; obtaining object data on which the verification rules depend based on the data resource information; determining the verification result corresponding to the verification request based on the verification rules and the object data, and generating a result display interface based on the verification result and the result display template; the result display interface is used to display the verification result. This method helps reduce the operational complexity of the pre-verification process.

This invention discloses an automated rule engine execution system and method for communication events, belonging to the field of communication technology. The system includes: collecting multi-source heterogeneous communication events; obtaining standard communication event objects through a dedicated rule meta-model for each communication event; loading a rule set; generating an abstract syntax tree through syntax parsing and pre-compilation; constructing a rule dependency graph and performing intersection and mutual exclusion detection to form a scheduling strategy containing priority, mutual exclusion whitelists, and execution order; locating a subset of candidate rules based on system context; determining the target rule through condition matching; encapsulating automated operations into atomic action units; and executing them concurrently or sequentially according to orchestration logic; simultaneously generating a unique execution trace ID to record the entire link log; monitoring anomalies in real time; triggering a circuit breaker if the anomaly rate exceeds the limit or execution times out; taking down abnormal rules and demoting their execution; evaluating the rule effectiveness and providing optimization suggestions after the session ends; this invention improves the efficiency of communication event processing and the stability of rule execution, ensuring reliable system operation.

This application relates to the field of drawing review technology, and more particularly to an artificial intelligence-based method, apparatus, system, and product for engineering drawing review. The method includes: acquiring drawing information and classification results of the drawing to be reviewed; selecting review rules from a preset review rule base based on the classification results to determine a first rule set; identifying each review rule in the first rule set to obtain a conflict rule group; prioritizing the review rules in the conflict rule group, retaining the review rule with the highest priority to generate a second rule set; and reviewing the drawing information using the second rule set to obtain a drawing review result. This application can resolve conflicting review rules retrieved from the rule base, determine a unique review rule for the same constraint object and the same constraint relationship, reduce the number of manual interventions caused by rule conflicts, and improve the efficiency of drawing review.

This invention relates to the field of intelligent matching and recommendation technology, and discloses a device intelligent recommendation system based on a large model. The system includes a parsing engine initialization module, a device recommendation rule evaluation module, a user input parsing module, a rule triggering decision module, a recommendation weight adjustment module, a recommendation content generation module, and a recommendation feedback processing module. First, the recommendation content weight vector for production equipment is initialized. Then, the validity of the rules for production equipment is pre-evaluated to generate a recommendation rule set. Using the optimized parsing engine and the recommendation rule set, a structured condition set is extracted from the user-input text, and recommendation rules are triggered. The recommendation content weight is optimized based on rule application priority. A comprehensive recommendation analysis is performed based on this vector to generate a device recommendation list. Finally, the optimal recommendation content weight vector is adjusted using a time decay mechanism. This invention can improve the accuracy of device intelligent recommendation based on a large model.

This invention provides a data query method and related apparatus to improve the accuracy of converting natural language data query questions into structured query statements. The method includes: using a natural language model to convert a received data query question related to a target application scenario into a target programming statement; parsing and rewriting the target programming statement using parsing rules set for the target application scenario to obtain a first structured query statement related to the target application scenario, wherein the first structured query statement includes at least an input, an output, and at least one rule associated with at least one of the input and output, as well as a rule type for the at least one rule; generating at least one data query task based on the rule type of the at least one rule; and querying a database according to the at least one data query task to obtain data corresponding to the data query question.

Techniques for accurately and efficiently assessing compatibility between resource users (e.g., patients) and resources (e.g., healthcare providers, facilities having certain medical equipment, etc.) obtain both user-side responses and resource-side responses to respective sets of queries (e.g., survey questions), and use those responses to compute a compatibility metric. The computation includes applying a rule set, which maps candidate responses of the resource user to candidate responses associated with the resource, including at least one rule that defines a one-to many or many-to-many mapping, i.e., maps a candidate user-side response to two or more candidate resource-side responses, or maps a candidate resource-side response to two or more candidate user-side responses. The rule set also defines computational rules that are associated with particular mappings.

The application discloses a kind of automated filling and checking method, system, product and medium of insurance information, and it is related to artificial intelligence field.The method comprises the following steps: in response to batch insurance instruction, the insured identity information is received and managed, and the independent data object is constructed to form the insured information set;Age is calculated by traversing the set and analyzing birth date;Age is used as a matching factor, matched with an insurance product rule base, to determine the applicable product plan range and premium calculation factor;Generate and bind a differentiated rule set for each data object;Based on context and differentiated rule set, generate an aggregated interactive interface;Receive input information in the exclusive problem area, and check according to the differentiated rule set;All input information that passes the check is summarized to generate an aggregated insurance order.Implementation of the technical solution provided in the application improves the efficiency of automated processing in the batch insurance scenario.

This invention discloses a method, device, medium, and product for parsing heterogeneous logs. The method includes: real-time acquisition of the current heterogeneous log and its corresponding heterogeneous log source identifier from the original heterogeneous log stream; acquisition of a log format description template and parsing rule set matching the heterogeneous log source identifier from a pre-built adaptation strategy knowledge base; format normalization processing of the current heterogeneous log based on the log format description template to obtain standardized log events represented by a unified intermediate representation structure; and parsing processing of the standardized log events using the parsing rules to obtain structured log records corresponding to the standardized log events. This technical solution improves the accuracy and reliability of parsing results of original heterogeneous log streams in complex practical application scenarios.

The application provides a method and device for event prediction based on a timing diagram rule, the method comprising: obtaining timing diagram data, and adding event prediction results of a machine learning model to the timing diagram data to obtain timing diagram extension data; extracting a subgraph for verifying prediction rule reliability from the timing diagram extension data according to a verification ratio; training a rule creator according to the timing diagram extension data and the subgraph to obtain a timing event prediction rule set; and obtaining a prediction event set according to the timing event prediction rule set and the timing diagram data. By embedding the machine learning model for event prediction into a rule-based association relationship system as a predicate, the association rule can not only use the existing machine learning model event prediction result, but also use a logical condition to improve the prediction result of the machine learning model, has stronger expression ability, and does not have to constrain constant interval time or have a common focus constraint on a graph pattern.

The application discloses an intelligent data visualization management system based on a large model, comprising: a request context generation module for generating request context data; a dual-domain symbol generation module for generating semantic domain symbol sequences and execution domain symbol sequences; an anchor mapping module for generating an anchor mapping table; a coupling rule generation module for executing an improved Sequitur algorithm to generate a semantic-execution coupling rule set; a grammar construction module for constructing a visualization task grammar; an instruction output module for generating data query instructions and chart rendering instructions and outputting target visualization results and execution feedback data; a rule splitting module for generating a conditional boundary sub-rule set; and a grammar graph updating module for updating the visualization task grammar. The application improves the stability, accuracy and rule evolution capability of data visualization task generation.

The application discloses an unstructured data automatic acquisition and classification intelligent method, relates to the technical field of data processing, and comprises the following steps: determining data sources, confirming data types and obtaining permissions; efficiently and compliantly obtaining target data from the data sources; improving data quality and eliminating noise interference through processing; extracting features from the data and constructing and training a classification model; the application automatically collects and processes unstructured data from various sources, and completes data classification through intelligent algorithms, so that the automatic acquisition and classification intelligent management of unstructured data are facilitated, the efficiency and accuracy of data processing are significantly improved through the introduction of automatic tools and intelligent algorithms, data security and compliance are taken into account, the application has higher automation and intelligent levels and stronger data processing capacity compared with traditional data acquisition and classification methods based on a rule set, and can better process complex and changeable data environments.

The application provides a test document detection method and device, electronic equipment and a computer readable storage medium. The method comprises: obtaining a document to be detected; analyzing the document by a large language model to obtain semantic information of the document; constructing a knowledge graph according to the semantic information; and determining a detection result of the document based on a preset rule set, the semantic information and the knowledge graph. The application deepens the examination level and improves the logical examination ability. Furthermore, the application can realize multi-dimensional document examination based on the rule set, finally realizes an efficient, transparent and interpretable test document examination scheme, and improves the overall examination quality.

The application provides an AI-assisted code generation method and system applied to a low-code platform, relates to the technical field of low-code platforms, and first acquires component requirement scenario information and analyzes to obtain a scene feature set, generates a dynamic evolution rule set in combination with platform real-time metadata; then calls an AI code generation module, inputs the scene feature set and the rule set, and generates initial component code; next, the initial code is deployed to a test environment, running data is collected and analyzed, iteration optimization instructions are generated to adjust the code and the rule set, and target component code is obtained; finally, the target code is embedded into a platform specified function module to complete code generation. The method can adapt to diversified scene requirements, combines with the real-time state of the platform, has self-optimization capability, and can improve the development efficiency and code quality of the low-code platform.

A computer-implemented method for anomaly detection when controlling a technical device by a controller includes a) providing input data, coding the input data aided by an auto-encoder to form coded data, and decoding the coded data aided by the auto-encoder to form output data, and determining and classifying a reconstruction error, b) determining a target variable from the reconstruction error if the reconstruction error exceeds a predefined reconstruction error threshold, c) providing a model based on artificial intelligence to an evaluator, d) determining, by the evaluator, a prediction for the target variable using the model and the classification of the reconstruction error, and providing the prediction to an analyzer, e) determining, by the analyzer, a rule for improving the reconstruction error from the prediction and a predefined rule set, providing the rule to the controller and controlling, by the controller, the technical device (TD) aide by the rule.

This application relates to the field of database technology, and in particular to a data reporting method, apparatus, device, medium, and program product based on intelligent data verification. The method includes: in response to acquiring submitted data, loading a pre-configured set of verification rules based on the form identifier corresponding to the submitted data; querying corresponding historical data values ​​according to cross-validation rules, logically comparing the target field value with the historical data value, and generating a cross-validation result; extracting basic field values ​​as input parameters according to complex verification rules, performing multi-level logical judgment operations, and generating a complex rule verification result; performing data type and format matching verification on specified field values ​​in the submitted data according to format verification rules, and generating a format verification result; generating verification result data, and returning the verification result data to the client, wherein the verification result data is used to identify erroneous units in the submitted data. This method can improve the management efficiency and effectiveness of reported data.

This invention discloses a structured parsing method for risk control intent based on knowledge constraints and dynamic arbitration, executed by an intent parsing server. The method includes: preloading a set of entity relationship constraint rules from a risk control knowledge graph; receiving natural language queries and parsing the initial intent, entities, and query type in parallel using a multi-task model; asynchronously semantically correcting these three elements based on the rule set; performing conflict detection and arbitration through a dynamic coordinator; and matching risk control scenario templates to generate structured semantic expressions. This method, by introducing domain knowledge rule verification and dynamic arbitration, solves the problems of inaccurate parsing and logical violations in professional risk control domains using general models. It transforms fuzzy natural language queries into precise, compliant, and executable structured instructions, improving accuracy, compliance, and system intelligence, while optimizing resource utilization efficiency and lowering the barrier to entry.

The application provides a kind of multi-level entity classification method and system based on large language model and rule engine, belong to data processing technical field.The method includes: the first filtering step, based on the exclusion rule set of dynamic update, the basic attribute data of entity is filtered;Second filtering step, after the weight distribution of the multi-dimensional feature data of entity, hierarchical matching analysis is carried out with feature library;Third filtering step, the integrated feature data and target classification definition information are input into pre-training large language model to carry out semantic reasoning determination, and output confidence;Classification mark and feedback step, according to the comparison result of confidence and preset threshold, determine the entity attribution and mark, and at the same time, the determination result is fed back to the feature library for self-optimizing update.The application realizes efficient and accurate entity classification through multi-layer progressive filtering architecture, has the advantages of high processing efficiency, high recognition accuracy, high intelligence, strong expansibility and the like.

The application relates to the technical field of artificial intelligence, in particular to a strategy generation method and device, electronic equipment and a storage medium, which are used to improve the generation efficiency and accuracy of a risk control strategy. The method comprises the following steps: obtaining risk assessment data to be mined; the risk assessment data comprises at least one of the following: object feature data related to risk assessment of at least one object and environment influence data related to an external environment; a data mining model is constructed based on the risk assessment data, and a model prediction result is obtained; the data mining model is used to identify potential laws related to a risk control strategy from the risk assessment data to perform risk assessment; the model prediction result is subjected to rule processing to generate an executable rule set; the rule set comprises at least one rule for risk assessment; and a risk control strategy for the at least one object is generated according to the rule set.

The application relates to the technical field of intelligent driving of vehicles, in particular to a multi-target tracking trajectory creation and deletion method and device, equipment and a storage medium, wherein the method comprises the following steps: judging whether a new obstacle is detected; if the new obstacle is detected, judging whether a preset association relationship exists between the new obstacle and a current existing obstacle trajectory; if the preset association relationship does not exist between the new obstacle and the current existing obstacle trajectory, creating a potential trajectory; when the logarithm of the existence probability of the potential trajectory is greater than a preset upper threshold, confirming the potential trajectory; and when the logarithm of the existence probability of the potential trajectory is less than a preset lower threshold, deleting the potential trajectory. Thus, the problem that many obstacles are miscreated or missed created due to the rules set by people is solved, compared with a traditional algorithm, the trajectory can be reasonably created and eliminated, and the reliability and stability of the system are improved.