43 results about "Match rule" patented technology

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.

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 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.

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.

The invention relates to a data detection method and device, computer equipment and a storage medium. The method comprises the steps that a field to be detected is extracted from a message to be detected, each rule field in a rule filtering table is matched with the field to be detected, the hit result of each rule field by the field to be detected is obtained, the rule filtering table comprises rule fields corresponding to candidate matching rules in a full-amount matching rule table, and the rule fields are matched with the candidate matching rules in the full-amount matching rule table; and when the hit result is that the to-be-detected field hits the target rule field in the rule fields, obtaining a target matching rule corresponding to the target rule field from the full-quantity matching rule table, and performing anomaly detection on the to-be-detected message according to the target matching rule. By adopting the method, the data anomaly detection efficiency can be improved on the premise of ensuring the anomaly detection reliability.

In an illustrative embodiment, an automated system links data files associated with loan submissions that have different identification attributes. The system may include computing systems and devices for receiving requests from a number of remote computing systems to identify loan products associated with a data file. The system can generate a matching input matrix comparing identification attributes from a first data file to identification attributes of candidate data files. The system can apply attribute matching rules to the matching input matrix to identify other data files that correspond to the same loan product as the first data file despite the data files having different identification attributes. The system can link data files corresponding to the same loan product within a data repository with a product linking key and output the linking key or other data for the loan product to a receiving computing system.

The embodiment of the application discloses a container keep-alive method, system, device and storage medium. The method comprises the following steps: obtaining basic data, resource data and service data of a target service container; according to a preset state exception matching rule, comprehensively obtaining an exception type based on multi-dimensional data; and performing keep-alive on the container according to a preset differentiated keep-alive strategy corresponding to the exception type. The method effectively solves the problem that the traditional mechanism cannot identify the resource overload to cause slow response and service logic exception and the like, can more timely and accurately find the container exception, takes targeted measures to ensure the stable operation of the service container, and further improves the overall availability of the system.

The invention relates to an automatic testing technology, and provides an automatic detection method and device, electronic equipment and a program product, and the method comprises the steps: obtaining a test case which is added with a command mark and a detection mark through a markup language; analyzing a test command according to the command mark, and analyzing an initial matching rule and detection information according to the detection mark; issuing a test command to the tested equipment, and obtaining an execution result echo of the test command; dynamically adjusting the initial matching rule to match the execution result and echoing to obtain a detection value; modifying the detection information by using the detection value to generate a detection rule; and executing the detection rule to obtain a detection result so as to determine whether the test script corresponding to the test case passes the test. The detection rule can be dynamically generated, the maintenance cost is reduced, and the test efficiency is improved.

A validity testing method and system for a data generator, and an electronic device. The method includes: obtaining a plurality of test targets and test backgrounds and a plurality of matching rules; obtaining physical fourth spatio-temporal feature data of a matching combination; forming a first mismatching combination and a second mismatching combination in both of which a background does not conform to the corresponding matching rule; respectively obtaining corresponding first spatio-temporal feature data and second spatio-temporal feature data; obtaining third spatio-temporal feature data by means of a data generator; comparing the third spatio-temporal feature data with the fourth spatio-temporal feature data, and obtaining a sub-score of the validity of the data generator; obtaining a plurality of sub-scores on the basis of the plurality of matching rules; and forming a total score of the validity of the data generator. The method assist evaluating data generator can for a desired data augmentation scenario.

The application discloses a kind of based on intelligent rule engine's clearing and accounting method and system, comprising: by visual interface configuration, including fund item, lending relationship, operation instruction and priority, accounting rule is formed into standardization rule base;Receive and analyze clearing instruction, extract instruction core element;With intelligent rule engine, based on instruction number, business scene, account state multidimensional matching rule, in combination with priority judgment and conflict resolution mechanism, determine accounting rule;Automatic execution fund transfer, generate accounting voucher and record log;Intelligently monitor and automatically dispose to abnormal condition.The application realizes the dynamic configuration and flexible extension of rule by decoupling accounting rule and system code, solves the problems of poor rule expandability, low instruction association accuracy and low abnormal processing efficiency in the prior art, and improves the automation level, accuracy and business adaptation efficiency of clearing and accounting.

This application provides a method and system for extracting technical and economic risk events based on monitored entities, belonging to the field of entity extraction technology. The method includes: performing entity recognition on multi-source scientific and technological texts, comparing and filtering technical and economic monitoring entities, and outputting a candidate monitoring entity list; extracting semantic segments using the candidate monitoring entity list as anchors, and determining event types based on trigger word matching rules; performing dependency parsing and semantic role labeling on the trigger word set, constructing a standardized event structure, extracting semantic relationships, and outputting a risk event candidate structure set; identifying chapter-level main events, aggregating paragraph-level related events to form a master-slave event structure; assembling event chains based on the master-slave event structure, and performing standardized output. This application can solve the technical problem of poor reliability in the extraction of economic risk events in the prior art, achieving the technical effect of improving the reliability of extraction.

This invention relates to the field of resource scheduling, and more particularly to a model scheduling method, apparatus, device, and storage medium based on information instructions. The method involves receiving information instructions to be processed, performing semantic parsing on the information instructions to obtain the task type and the constraint features associated with the task type; based on the task type, calling a matching rule set corresponding to the task type from a preset strategy library, the matching rule set including multiple capability evaluation dimensions and initial weights for each capability evaluation dimension; obtaining the capability scores of all available AI models on each of the multiple capability evaluation dimensions; adjusting the initial weights in the matching rule set according to the constraint features to obtain the adjusted weights for each capability evaluation dimension; weighting the capability scores of multiple available AI models using the adjusted weights to obtain the comprehensive matching degree of each available AI model relative to the information instruction; and assigning the information instruction to the available AI model with the highest comprehensive matching degree for execution.

A system for a simulated stock exchange (a digital twin) and methods for a plurality of test users performing forward testing of order transactions are described. The core of the system is comprised of an AI engine to generate and / or update a limit order book (LOB) according to criterion such as received orders, market conditions and time frame, and a matching engine that executes orders according to exchange's order matching rules. Liquidity generator is an optional component that adds large number of realistic orders to the system to increase liquidity. The AI engine is trained with time-stamped historic order data. The test user's access to the system is through a client application and uses open trading protocols to send orders and receive market data updates. The AI model uses deep learning with an autoregressive generative model for LOB transitions.

The embodiment of the invention provides a routing request scheduling method and device, electronic equipment and a storage medium, and the method comprises the steps: responding to a set top box service request, analyzing the set top box service request, and determining a matching rule index; matching the scheduling strategy based on the matching rule index, and determining a target scheduling strategy; analyzing the target scheduling strategy to determine a schedulable node group address; and issuing the set top box service request to the schedulable node group address. According to the embodiment of the invention, scheduling can be carried out under the same scheduling dimension, and the method is more flexible so as to adapt to scheduling requirements of different scenes to complete scheduling tasks.