60 results about "Match rule" patented technology

The invention relates to a multi-agent scheduling method and system based on task intention matching. The method comprises the following steps that S1, tasks are received and analyzed; s2, intelligent agent matching candidates are obtained; s3, selecting an optimal agent by a scoring mechanism; s4, task assignment, execution monitoring and result acquisition; s5, performing reflection evaluation and strategy updating: dynamically updating an intelligent agent score, and adjusting a task label matching rule or other scheduling parameters so as to optimize a distribution decision of a subsequent task; and S6, result combination and output: when the task comprises a plurality of sub-tasks executed by a plurality of intelligent agents, the results are verified, sorted and combined. Compared with the prior art, the method has the advantages that the task target can be dynamically analyzed, the optimal agent can be intelligently matched to execute the task, and the scheduling strategy is continuously optimized through feedback after the task is completed, so that the task execution efficiency and effect of the multi-agent system are remarkably improved, and the accuracy, the adaptability and the intelligent level of task allocation are improved.

The invention provides a match alliance platform management system and method, and the system comprises a match authentication module constructed by a block chain, an AI-driven qualification auditing module, a process management module, a convolutional neural network, a big data analysis module, and an RBAC authority management module. Wherein the match authentication module dynamically analyzes and stores authenticated match rule data through an intelligent contract, and realizes rule version tracing by using an encrypted hash chain; the AI-driven qualification auditing module integrates a natural language processing engine to analyze the selection standard and construct a multi-dimensional evaluation model, and adopts a machine learning algorithm to analyze historical data of athletes to generate a visual qualification report; the process management module supported by cloud computing automatically generates an application process based on a rule engine, adopts a Monte Carlo algorithm to execute multi-constraint drawing, and constructs a directed graph model to dynamically generate a schedule topological structure containing a three-person rotation time sequence.

The invention discloses a policy matching and pushing method and system based on a large model technology, and relates to the technical field of big data processing, and the implementation of the method comprises the following steps: constructing a multi-dimensional enterprise portrait library comprising enterprise basic information, honor information, qualification information, judicial risks, administrative punishment and project information; for the first policy, vectorizing a policy text and an enterprise portrait through an Embedding model, calculating semantic similarity and generating a recommendation list; for a non-first policy, policy conditions are deduced based on a historical reward list, condition credibility is adjusted through a large model and a machine learning model, and recommendation priorities are calculated in a weighted manner; and a data real-time updating and model feedback optimization mechanism is established, and the matching precision is dynamically improved. According to the method, cross-modal semantic alignment can be realized, recommendation accuracy is improved, matching rules are dynamically updated, and the method can adapt to real-time changes of policies and enterprise data.

The invention provides a two-hop incremental interface consistency verification method and system based on a knowledge graph, and the method comprises the steps: 1, carrying out the language analysis of a modified source file, and extracting an interface entity; 2, mapping the interface entity into a language-independent meta-model, and writing the language-independent meta-model into a knowledge graph; 3, executing a two-hop breadth-first traversal algorithm by taking a modified node in the knowledge graph as a starting point to obtain an affected sub-graph; 4, a hot-pluggable rule set is operated on the affected subgraph for verification, the rule set comprises a parameter number matching rule, a type compatibility rule, a version number increasing rule and a field deletion forbidding rule, and if verification is illegal, an error report is generated, and a blocking instruction is output; and if no violation exists in the verification, merging the affected sub-graphs back to the knowledge graph cache. According to the method and the device, online faults caused by field missing during operation are avoided, and the influence of back-end change on the front end is automatically detected and blocked.

The invention provides a rule processing method. The method comprises the following steps: determining a corresponding target rule file according to a preset inquiry type; and dynamically adjusting rules in the target rule file according to the attribute information of the inquiry type to obtain a target rule. According to the scheme, firstly, only the target rule file related to the inquiry type is obtained, the number of the matched rule files is reduced, and secondly, the processing mode of the rules in the target rule file is dynamically adjusted, and the response time consumption of rule matching is shortened.

The invention discloses an e-commerce data intelligent processing method and system based on dynamic flow optimization. The method comprises the following steps: acquiring and analyzing multi-platform e-commerce data, and converting the multi-platform e-commerce data into a standardized format; constructing a matching rule by adopting a decision tree algorithm, and performing classification and priority marking on the data; the data flow is dynamically scheduled based on the priority, so that the high-priority data is executed preferentially; data are processed through parallel nodes, performance indexes such as network delay and throughput are monitored in real time, and data stream processing efficiency is optimized in combination with a dynamic scheduling algorithm. The system correspondingly comprises a data standardization module, a rule matching module, a dynamic marking module, a parallel processing module and a monitoring scheduling module, efficient and self-adaptive processing of the multi-source e-commerce data is achieved, and the data processing real-time performance and the system throughput are remarkably improved.

This invention discloses a traffic marking method and apparatus based on rule matching. (i) If a program script is set for the matching rule, the program script is executed first for matching; (ii) If the script execution result is true, it indicates a match, and the request traffic is marked according to the pre-set marking; (iii) If it returns false, it indicates no match, and the traffic is not marked; (iv) The parameters of the script program are the request parameters of the system interface, which are dynamically passed to the script program when the script is run, and then the complex logic of the script program is used to finally give the result of whether to mark; (v) If no script is set, the basic rule information provided is used for matching and marking. This invention uses a combination of basic rules and advanced scripts, which can be flexibly applied to meet the marking requirements of different scenarios.

The invention relates to the technical field of network operation and maintenance, and provides a multi-agent discovery method and device in an operator scheduling scenario, and the method comprises the steps: obtaining a command scheduling instruction inputted by a user; performing agent self-matching on the command and dispatch instruction according to a matching rule configured by each agent, wherein each agent is configured with at least one matching rule; under the condition of successful self-matching, determining the matched intelligent agent as a target intelligent agent; under the condition that self-matching fails, inputting the command and dispatch instruction into a pre-trained agent decision-making model to obtain a target coding text output after the agent decision-making model identifies the intention of the command and dispatch instruction, and under the condition that the target coded text is matched to a to-be-matched coded text configured in the matching rule of any agent, determining the any agent as a target agent. According to the method, the target agent matched with the command and dispatch instruction input by the user can be quickly and accurately found in a low-delay manner.

The invention discloses a task resource allocation method and device, equipment and a storage medium. The task resource allocation method comprises the steps that in response to a task processing request, resource pool matching is conducted according to labels carried by a task and matching rules of all resource pools, and the matching rules are set based on the labels and support logical operation among the multiple labels; and according to the task type and the algorithm requirement of the task, allocating resources in a resource pool matched with the task to process the task. In this way, simplified allocation of algorithm task resources can be achieved.

The invention provides a dual-carbon transaction service platform with a transaction information accurate matching function, and relates to the technical field of carbon transactions, and the dual-carbon transaction service platform comprises a sequentially nested verification chain formed by a token issuing unit, an area pre-detection unit, a time window response unit, a data interoperation unit, a manual verification unit and an electronic filing unit which run in sequence. The platform carries the mapping information by using the digital token, the category code corresponds to the carbon quota category, the aging state code is bound with the effective time period, and the regional feature code is associated with the regional emission factor data. During verification, region consistency is verified through an algorithm, period effectiveness is judged through system time, kernel exposure is triggered through a data matching rule, finally, an authenticator carries out visual comparison and applies digital marks, and whole-course data is recorded and evidence-stored through an electronic filing unit.

The invention belongs to the technical field of data processing, and discloses a policy service accurate pushing method and system for medium and small enterprises. Comprising the following steps of: constructing a matching rule base covering four types of conditions of regions, scales, industries and products by performing clause-level atomization disassembly and multi-dimensional knowledge expansion on enterprise industry and commerce information on policy texts, and realizing cross-dimensional consistency matching of policy conditions and enterprise characteristics; according to the method, construction of a logical dependency relationship graph is introduced, atomic judgment conditions are used as graph nodes, a core admission chain is identified through dependency strength weights and topological sorting, matching confidence is quantified based on path weights and a logical propagation algorithm, and enterprise policy applicability and information gaps are accurately identified; the method has intelligence and accuracy, deep semantic analysis and applicability evaluation can be carried out on policy terms, and personalized difference pushing is effectively achieved.

The present application relates to the technical field of data matching, and provides a heterogeneous rule matching method and device. In the present application, rule hierarchy structure and other information are abstracted into a rule model, and the rule model is constructed using a tree structure according to specific predetermined rule data, so that the problem of poor code reusability for similar heterogeneous matching rules is solved. By constructing a rule filter, the matching efficiency is improved. During matching, only the rule model is used to match according to the logical relationship in the rule model, so that the use of all original data to be matched to traverse all rules for sequential matching is avoided, and the matching efficiency is higher. Further, the predetermined rule data is integrated and classified by constructing an index, so that the matching efficiency is further improved, and the probability of matching errors is reduced.

The invention provides a transaction matching method and system and related equipment, and the method comprises the following steps: obtaining transaction data, determining a plurality of matching rules matched with the transaction data, sorting the plurality of matching rules based on the score of each matching rule, and obtaining a sorting result, the score of each matching rule is in direct proportion to the refining degree of the condition in each matching rule, determining the transaction account used by the transaction data based on the sorting result, configuring the score representing the refining degree for each rule, and when the transaction occurs, if the number of the rules successfully matched with the transaction data is multiple, determining the transaction account used by the transaction data. At the moment, the transaction account can be determined by selecting the rule with the highest refining degree based on the score, so that the problem that the transaction cannot be carried out due to the fact that the matching result comprises a plurality of accounts is solved, manual participation is not needed, and the user experience is improved.

According to the abnormal data analysis method and the abnormal data analysis platform provided by the invention, when the abnormal data analysis platform receives the alarm information published by the alarm system, the corresponding abnormal analysis task script can be matched for the alarm information based on the pre-configured matching rule; as the exception analysis task script is configured according to different application scenes in the service system, when the exception analysis task script obtained after matching runs, the exception reason of the alarm information can be quickly and accurately positioned, and an accurate exception data solution is provided for a user.

The present application relates to the field of receivables management, in particular to a kind of receivables automatic clearing management method, the receivables automatic clearing management method is by obtaining the data of the proceeds of the project pre-processing, and according to the matching rule of multilevel is matched to obtain data matching result, according to scene matching condition, the data matching result is matched transaction scene to avoid artificial transaction scene judgment, the data matching result of transaction scene carries out data check, and through clearing condition identification data check result, the proceeds of the project is cleared step, and using confidence level grading condition is graded and data confirmation, and the proceeds of the project after data confirmation generates accounting voucher, simultaneously marks its reconciliation state and generates matching number, through data check, the association between receivables information and proceeds information, avoid artificial repetitive operation account reconciliation, so as to avoid reconciliation delay and improve reconciliation efficiency.

The invention provides a label-based message service engine, and the engine comprises a label subscription management module which is used for processing a label subscription request of a user, constructing a matching rule tree of the user, and registering the matching rule tree; the labelled message processing module is used for extracting a label of the message, constructing a label vector of the message according to the label, and constructing a label index; the label matching engine is used for extracting a label vector of a new message when the new message arrives, calling a label matching algorithm based on a label index to traverse all registered matching rule trees, and determining a successfully matched user list; and the message distribution module is used for pushing the new message to the message queue of each user in the user list. According to the method and the device, accurate matching between the message and the complex subscription condition of the user is realized based on a label mechanism, so that the message received by the user better meets the requirement, the efficiency in the matching process is improved in combination with the matching rule tree and the multi-level label index, and an efficient pushing effect in a complex subscription scene is completed.

The application discloses a data query method and device based on regular matching, equipment and medium, the method comprises: obtaining a query request containing query data; the query data contains at least one first string; according to the preset regular matching rule and the preset association sequence, all first strings in the query data are regularly matched, and a first hash field with a hash structure is generated; according to the first hash field, a second hash field matched with the first hash field is queried in the regular matching dictionary of the cache database; according to the storage code associated with the second hash field, the relational data corresponding to the query data is obtained from the relational database. The application improves the speed and efficiency of data query.

A method comprising receiving, at a first computing system, encrypted identifiers, performing, by the first computing system, a concealing operation on the encrypted identifiers to produce concealed encrypted identifiers, wherein the concealing operation conceals the encrypted identifiers from the first computing system and a second computing system but enables matching between the concealed encrypted identifiers, decrypting, by the second computing system, the concealed encrypted identifiers to produce concealed identifiers, analyzing, by the second computing system using one or more match rules, the concealed identifiers to generate one or more associations between the concealed identifiers, and generating, by the second computing system, one or more universal identifiers based on the one or more associations.

The application discloses a kind of methods and systems for generating construction scheme related to safety red line rule embedding and real-time triggering, the method for generating construction scheme includes: S1: engineering type identification and rule set loading;S2: large language model streaming output and segment division, the generation output of the token reception model is received;S3: real-time rule matching, for each input generation fragment, condition evaluation of each rule is executed in active rule set, whether the current fragment and its context meet the trigger condition of rule is judged;S4: rule intervention, receive the matched rule list output in step S3, execute the intervention action defined by each rule in turn according to priority from high to low;S5: corrected content backwriting and generation, after completing intervention operation, the corrected text fragment is backwritten to generation content buffer area, and the content generated in sequence and verified before is spliced, to form continuous text meeting safety requirements, as construction scheme output.

The present application provides a transaction matching method, a system, and a related device. The method comprises the following steps: obtaining transaction data, determining a plurality of matching rules matching the transaction data, and sorting the plurality of matching rules on the basis of the score of each matching rule to obtain a sorting result, wherein the score of each matching rule is in a positive proportional relationship with the granularity of a condition in each matching rule; and on the basis of the sorting result, determining a transaction account used by the transaction data. A score representing the granularity is configured for each rule, and when a transaction occurs, if there are a plurality of rules successfully matching transaction data, the rule having the highest granularity can be selected on the basis of the score to determine a transaction account, thereby solving the problem of transaction failures caused by matching results comprising a plurality of accounts; moreover, no human participation is required, thereby improving use experience of users.

The application relates to an optimization method and device for web intrusion detection, computer equipment, a storage medium and a program product. The method comprises the following steps: loading a rule database, distributing matching rules in the rule database to multiple matching processes, determining a target process from the multiple matching processes according to the danger degree of a source IP corresponding to current HTTP traffic, performing rule matching on the current HTTP traffic through the target process, performing rule evaluation on the matching rules based on the matching result of the rule matching, updating the danger degree of the source IP, updating the rule database according to the result of the rule evaluation, and distributing the updated matching rules to the corresponding matching processes. The method can select appropriate processes for rule matching, better adapt to changes in the network environment and actual security requirements, and improve the accuracy and timeliness of security detection.

The invention discloses a question and answer task evaluation method and system based on a mixed expert structure, and belongs to the field of artificial intelligence, and the method comprises the steps: obtaining a reply generated by a to-be-tested large language model for a question, and extracting a short answer from the reply in combination with the question; obtaining a matching result between the short answer and a real answer of the question according to a predefined matching rule; under the condition that the matching result is complete matching or partial matching and the predicted answer does not exceed or is wrong, giving an evaluation score to the reply based on score setting of a predefined matching rule; and generating an evaluation score of the reply by using an evaluation model based on a hybrid expert structure under the condition that the matching result is completely mismatched or an error exists. According to the method, the high accuracy of reply evaluation is ensured, and meanwhile, the cost benefit is relatively high.

The application belongs to the technical field of artificial intelligence, and relates to a business dispatching method, which comprises the following steps: obtaining a business label set of a target insurance business; according to a semi-inclusion matching rule, multi-dimensional business labels in the business label set are aggregated into a business main label; according to a matching order in a preset priority layer, a first business label is extracted from the business main label in sequence, a first expert label is extracted from an expert label set based on the first business label, and a first matching expert and a first matching quantity are obtained; whether the first matching layer is a dispatch output layer is determined according to the first matching quantity; and if the first matching layer is the dispatch output layer, a target dispatch expert is determined from the first matching expert. The application also provides a business dispatching device, a computer device and a storage medium. The application can be applied to a business management program system of finance and insurance, can match professional resources based on business characteristics, and solves the problem of low claim settlement efficiency and quality caused by mismatch of professional resources.

The invention relates to the field of account receivable management, in particular to an automatic account receivable settlement management method, which comprises the following steps of: acquiring account receivable data of a project for preprocessing, and performing hierarchical matching according to a multi-hierarchical matching rule to obtain a data matching result; matching the data matching result with a transaction scene according to a scene matching condition to avoid manual judgment of the transaction scene, performing data verification on the data matching result of the transaction scene, identifying a data verification result through a settlement condition, and performing settlement on a project payment item. The method comprises the following steps of: carrying out classification and data confirmation by utilizing a confidence classification condition, generating an accounting voucher for a project collection item after data confirmation, marking an account checking state to generate a matching number, and carrying out association between receipt receivable information and collection item information through data checking, so that repeated manual operation of account checking is avoided, and the efficiency of account checking is improved. Therefore, account checking delay is avoided, and account checking efficiency is improved.

The application discloses an object group expansion method, device and medium, and relates to the technical field of data processing. The method aims at the problem that the existing group expansion method is rigid in matching rules and causes insufficient coverage, and proposes a dynamic iteration expansion scheme. A plurality of seed object sets associated with different identifiers are initialized. For the set to be expanded, the feature differences are identified by comparing other seed sets with the same identifier, and the matching weight of the difference features is dynamically reduced accordingly. Then, based on the adjusted weight, candidate objects are retrieved and matched from the basic information library to join the set. Finally, the feature representation of the seed set is updated according to the features of the newly added objects, and the iteration is repeated until the termination condition is met. The application realizes efficient and adaptive discovery and expansion of potential objects with reasonable feature variation under the premise of ensuring target consistency.

The invention is suitable for the technical field of data management, and provides a material master data optimization and standardization processing method and system based on a multi-dimensional matching rule, and the method comprises the following steps: S1, data preparation: collecting and sorting material master data, and ensuring that the data has fields matched with a standard library; s2, standard library construction: constructing a standard library containing standard data according to national standard and line standard documents, and regularly updating and maintaining the standard library; and S3, defining a matching rule: according to business requirements and data characteristics, defining a multi-dimensional matching rule including accurate matching and fuzzy matching. According to the material main data optimization and standardization processing method and system based on the multi-dimensional matching rule provided by the scheme, the problems of repeated codes, error codes and missing filling are mainly solved, and the data accuracy is ensured; material architecture optimization is completed, the encoding technology attribute problem is solved, and the reasonability of a data structure is improved; and comprehensive optimization and cleaning of the data are realized.

This invention discloses a question-answering task evaluation method and system based on a hybrid expert structure, belonging to the field of artificial intelligence. The method includes: acquiring the response generated by a large language model to a question, and extracting a short answer from the response in conjunction with the question; obtaining the matching result between the short answer and the true answer to the question according to predefined matching rules; assigning an evaluation score to the response based on the scoring settings of the predefined matching rules when the matching result is a complete match or a partial match and the predicted answer has no errors or excesses; and generating an evaluation score for the response using an evaluation model based on a hybrid expert structure when the matching result is a complete mismatch or contains errors. This invention achieves high accuracy in response evaluation while also being cost-effective.

Devices, systems and methods are provided for managing records. One method involves constructing a fuzzy match graph data structure with edges between different field values for a fuzzy matched field of a plurality of records in accordance with a matching rule, assigning unique identifiers to different subgraphs of field values within the fuzzy match graph data structure, determining a match key value associated with a respective record based on a respective unique identifier assigned to a respective subgraph of field values including a respective field value for the fuzzy matched field of the respective record, constructing a heterogenous graph data structure having edges between the respective match key values associated with the respective records of the plurality of records, identifying a subset of related records using the heterogenous graph data structure, and performing one or more actions on the subset of related records at a database system.

The invention relates to an intelligent reconciliation method, system and device based on a dynamic link and a storage medium. Link parameters are dynamically loaded, a data link connected with an external system is created, and the dynamic link is generated; obtaining order data from an enterprise internal system through the dynamic link; acquiring bill data from a third-party system through the dynamic link; matching the order data with the bill data according to a preset multi-level matching rule, and performing account checking and account sales processing on the successfully matched data; according to the account checking method, multiple internal and external systems are flexibly accessed, the manual account checking efficiency is improved, and the account checking error rate is reduced.

The present application relates to a kind of HTTPS traffic monitoring method and device based on rule tree, the method includes: based on machine learning, matching rule base is constructed;From the matching rule base, balanced binary rule tree is constructed;Through the balanced binary rule tree, according to the matching rule base, service conversion is carried out to HTTPS service;After service conversion, HTTPS service is monitored to HTTP traffic.The present application is converted to HTTP service after corresponding rule matching based on rule tree on agent, realizes real-time HTTPS service traffic degradation, so as to the real-time monitoring of HTTP traffic after degradation is realized to the real-time monitoring of HTTPS traffic, improves the monitoring accuracy.