269 results about "Business data processing" patented technology

The invention provides a service data voice processing method and system based on artificial intelligence, and relates to the field. The service data voice processing method based on artificial intelligence comprises multi-mode voice preprocessing, domain enhancement voice recognition, knowledge graph driven semantic analysis, a dynamic dialogue management mechanism and a closed-loop feedback optimization system. According to the method, high-precision recognition, semantic understanding and structured processing of the service voice data are realized by fusing the domain knowledge graph, the dynamic model optimization and the context sensing technology, and the service data processing efficiency and accuracy are improved; secondly, the system comprises a voice acquisition and preprocessing module, an AI voice processing module, a business data processing module, a model optimization module and a data interface module, the efficiency and accuracy of business data voice processing can be remarkably improved, and the system is suitable for various professional scenes such as finance, customer service and medical treatment.

The invention provides a data processing method based on request interception, which comprises the following steps of: intercepting a calling request for marking a service method through a request interception mechanism, preposing a decision point of service logic, and selecting whether the service method is executed or not according to a request context. According to the method and the device, the business rules are stored in the configuration center, external rule configuration is performed, the business rule expressions are pre-stored in the configuration center, dynamic acquisition is performed based on the rule identifiers, decoupling of the business rules and the codes is realized, the business rules can be configured independent of the codes, and flexible business processing can be realized only by modifying the expressions of the corresponding rules in the configuration center. The problems of code expansion and difficult maintenance caused by business rule change in a multi-channel environment are effectively solved, so that the flexibility and maintainability of a business data processing system are improved. The method can be applied to a business processing system in the financial field or the medical field, so that the flexibility of the business processing system in the financial field or the medical field is improved.

The invention discloses an intelligent processing method for automatic settlement of review labor reward of a review expert, and belongs to the technical field of business data processing, and the method comprises the steps: obtaining text revision trajectory data and cooperative interaction data of the review expert, and generating a review behavior feature vector; performing recessive workload analysis on the review behavior feature vector to generate a quality weight factor; obtaining project environment parameters, and calculating to obtain a reward amount according to the project environment parameters, the quality weight factor and a preset settlement coefficient; performing exception verification on the reward amount, if the verification is passed, executing payment operation, and otherwise, triggering a manual rechecking process; and updating the settlement coefficient according to the feedback data after payment. According to the method, the reward is dynamically calculated by quantitatively reviewing the behavior characteristics and fusing the environmental parameters, and an exception verification and closed-loop optimization mechanism is established, so that fair and efficient full-process automatic settlement can be realized.

The invention relates to a business data processing method and system, equipment and a medium. The method comprises the following steps: preprocessing multi-source heterogeneous cross-domain economic data to generate a standardized data stream; semantic drift in the standardized data flow is detected in real time, and a detection result is generated; semantic alignment judgment is carried out based on the detection result, and a dynamic alignment signal is generated; performing incremental training of a mapping model by using the dynamic alignment signal to generate an updated cross-domain mapping model; and finally, performing mapping conversion on the data stream based on the updating model, and outputting service data with unified semantics. By adopting the method, the semantic change in the economic data can be responded in real time, the problems of semantic drift detection lag, long model updating period and high maintenance cost in the traditional technology are effectively solved, and the accuracy and timeliness of cross-domain economic data processing are remarkably improved.

The embodiment of the invention discloses a product business data processing method and device for an ERP business scene and a medium, and relates to the technical field of ERP, and the method comprises the steps: obtaining historical sales data, supply chain data and external environment data of a target product in an ERP system under the triggering of a business index prediction request, and obtaining a business index prediction result of the target product based on the supply chain data; determining a plurality of dynamic time scales corresponding to the target product to determine a multi-dimensional feature set corresponding to each dynamic time scale; determining a business index linear predicted value and a nonlinear residual sequence through an ARIMA model and each multi-dimensional feature set; according to the external environment data, performing decomposition prediction on the nonlinear residual error sequence to determine a reconstructed residual error sequence, and determining current service index prediction data corresponding to each dynamic time scale based on the service index linear prediction value and the reconstructed residual error sequence; and performing multi-scale fusion on the business index prediction data corresponding to each dynamic time scale, and determining target business index prediction data of the target product.

The embodiment of the invention provides a business data processing method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: generating a query semantic vector according to a data query problem; performing table data query operation in the business knowledge base according to the query semantic vector to obtain data table information; generating an initial cue word according to the data table information; obtaining a to-be-executed structured query statement according to the initial cue word, the data query problem, the business database and the fine-tuned proprietary large model; inputting the to-be-executed structured query statement into a preset executor, and when the execution result of the preset executor executing the to-be-executed structured query statement is successful, executing query operation from the business database to obtain preliminary result data; and performing presentation processing according to the preliminary result data to obtain to-be-presented data. Conversion from a natural language data query problem to a structured data query problem is realized, and the technical effect of enhancing the accuracy of a query result is achieved.

The invention discloses an engineering building construction quality analysis system and method based on data processing, and belongs to the technical field of commercial data processing and intelligent decision, and the system comprises a causal relationship graph construction module which is used for fusing multi-source monitoring data to construct a causal relationship graph; the risk profile construction module is used for performing reverse deduction and forward simulation and constructing a prospective quality risk profile; the multi-target collaborative optimization module is used for solving a Pareto optimal equilibrium solution set; the quality pre-control instruction generation module is used for instantiating a dynamic quality pre-control instruction; the efficiency evaluation and attribution correction module is used for updating the causal relationship graph; and the evolution auditing and causal knowledge distillation module is used for auditing historical updating of the atlas and distilling a core causal rule set. According to the method, risk deduction and simulation are carried out by constructing the dynamic causal relationship graph, and multi-objective optimization and closed-loop feedback correction are combined, so that prospective identification and collaborative intelligent pre-control of the project quality risk can be realized.

The invention relates to the technical field of engineering project management, and discloses an engineering project supply chain collaborative management system, which comprises a unified data interface module used for acquiring multi-source business data from heterogeneous information systems of an engineering project general package party, a sub-package party, a material supplier and a logistics service provider, processing the multi-source business data into a standardized business data model; and a business process management module. By adopting the technical scheme that a unified data interface module and a workflow engine cooperatively work, the technical effects of connecting information systems of all participants of a supply chain and realizing automatic synchronization of purchasing, inventory and construction progress data and linkage of a business process are achieved; compared with the technical scheme that each party adopts an incompatible information system and depends on manual information transmission in the prior art, the defect that the accuracy of a project plan is damaged due to difficulty in collaborative operation caused by data obstruction is overcome.

The invention relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, and a multi-task prediction model based on multi-source historical business chain data training graph neural network and Transform fusion. A plurality of groups of lane layout and event configuration schemes are generated in combination with user real-time operation captured by a design interface, an optimal scheme is screened through simulation evaluation and then is visually displayed, finally, visual lane modeling is executed according to user feedback, and through automatic data processing, high-precision model prediction, real-time interaction optimization and visual modeling, the optimal lane layout and event configuration scheme is obtained. According to the method, the service chain design efficiency and quality are improved, meanwhile, artificial experience deviation is avoided through model prediction based on historical data, the comprehensive requirements of complex equipment development for real-time performance, reliability and resource efficiency are met, and efficient technical support is provided for landing of model-based system engineering in the field of complex equipment.

The invention provides a method for dynamically dividing data into buckets. The bucket redistribution operation mode is dynamically determined by obtaining the bucket distribution heat parameter of the service data and the load parameter of the computing node in real time. And based on joint judgment of the popularity and the load, triggering a bucket splitting or merging operation, generating a target bucket scheme and storing an incremental snapshot, thereby ensuring that the affiliation relationship of the business data in the bucket adjustment process is clear and traceable. The incremental snapshot provides a core basis for lossless recovery of a subsequent calculation state by recording bucket metadata, calculating offset and intermediate result data. Furthermore, by predicting an expected load parameter of a computing node and combining a target bucket distribution scheme, the bucket distribution is dynamically distributed to a load matching node, and the problem of resource distribution stiffness of static bucket distribution is solved. The computing node recovers the business data processing flow based on the incremental snapshot, so that repeated calculation or loss of data caused by bucket adjustment is avoided, and the real-time data processing efficiency, the resource utilization rate and the business continuity are remarkably improved.

The invention discloses a cross-system service data processing method, device and equipment, a medium and a product. The cross-system business data processing method comprises the following steps: establishing a dynamic field mapping relationship between an integration layer and a plurality of target business systems; extracting capital construction business data from the target business system through the integration layer according to the dynamic field mapping relationship, and performing standardization processing to obtain standard business data; aiming at each stage of the capital construction project, constructing corresponding index data to obtain an index system; on the basis of an index system, index penetration query is carried out on standard business data, and a linkage management and control mechanism of an index abnormal item and an infrastructure project three-dimensional model is established; on the basis of the multiple access roles, corresponding visual billboards are distributed, and the visual billboards support index display; and based on a preset data quality rule base, performing quality evaluation on the standard business data, and identifying data abnormal items. According to the technical scheme provided by the embodiment of the invention, integrated management and control of cross-system business data are realized.

The invention discloses an air ticket order optimization method and system combined with big data, and relates to the technical field of air ticket business data processing. The air ticket order optimization method comprises the steps of multi-source heterogeneous data acquisition, federal feature fusion processing, dynamic pricing decision making, user implicit demand mining and real-time risk early warning and resource allocation, and has the advantages that the system supports real-time integration of aviation operation data, external environment data, user behavior data and market dynamic data; the limitation that a traditional system only depends on data in a single field is broken through, scattered multi-source data is converted into global features reflecting market trends, user demands and potential risks through a federal feature fusion technology, multiple influence factors such as flight transport capacity, user preferences and external events can be considered in the decision making process, and the decision making efficiency is improved. And the decision-making capability of the system in a complex scene is effectively enhanced.

The invention belongs to the technical field of artificial intelligence, and provides a service processing method and system based on multi-agent collaborative group chat in order to solve the problem of poor accuracy of a service data processing result. The business processing method based on multi-agent collaborative group chat comprises the steps of constructing a business data processing chat group; receiving a current user message of a human user, calling an analysis manager agent to perform intention analysis on the current user message, and judging whether an intention analysis result belongs to a current service data processing task or not; if yes, an analysis manager agent is called to distribute a user message to a corresponding service expert agent to reply and judge whether manual intervention is needed or not until the current service data processing task is completed; otherwise, calling an analysis manager agent to judge whether the current user message is an analysis demand, and if yes, responding to the analysis demand until the analysis demand is completed. Manual correction and intervention can be carried out at any time in a chat group form, and the accuracy of a service data processing result is improved.

The present disclosure provides a business data processing method and device, equipment and medium, which are related to the technical field of artificial intelligence and can be applied to various scenes such as cloud technology, artificial intelligence, intelligent transportation and auxiliary driving. The method comprises: in the case of detecting a business access request for indicating access to a first preset business object, obtaining a first access credential matched with the business access request; the first access credential is determined according to dynamic factor data and static factor data of the terminal of the business management client; sending a first credential acquisition request for indicating obtaining a second access credential to the management server, the first credential acquisition request comprising the first access credential; obtaining a first credential acquisition result determined by the management server based on the first access credential and an access control strategy list; and performing business access control based on the first credential acquisition result. Through the method, the business access efficiency and security are improved.

The application relates to a business data management method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the following steps: obtaining business data of a product, and performing feature extraction to obtain an extracted business feature vector; the business data comprises an order quantity, a number of minimum stock units of the product, a quantity of the minimum stock units and a storage timestamp; different products are clustered based on the business feature vector to obtain a preliminary clustering result; a graph neural network is constructed by taking product orders and minimum stock units as nodes, and the preliminary clustering result is further clustered and merged by using the trained graph neural network to obtain a final clustering result; and the corresponding shortest picking path is calculated according to the final clustering result. The method can improve the utilization rate of business data, thereby reducing the cost and accelerating the efficiency of business data processing.

The embodiment of the invention provides a business data processing method and device, a storage medium and a program product, and the method comprises the steps: obtaining business target data and actual business data of each employee; sending the business target data and the actual business data to a data warehouse after each preset synchronization time; and obtaining and calculating actual business data in the data warehouse by using a pre-obtained calculation model, comparing an actual business result obtained after calculation with the business target data, and generating a business index progress of each employee. According to the business data processing method provided by the embodiment of the invention, the business data of multiple employees can be processed in batches in real time, and the data processing efficiency is improved.

The present application provides a method, device and storage medium for processing abnormal business data, wherein the method comprises: obtaining multiple business data of a business, the cycle length T of each business data and the collection time of each business data; based on the time sequence position of the collection time of each business data in the data cycle of the business data, grouping the business data with the same time sequence position into an extended set; for each business data y i , the business data y i The acquisition time t i Before and after each W d Each business data in the extended set to which the business data corresponding to the collection time belongs, business data y i Each business data in the extended set and the collection time t i Before and after each W s The business data corresponding to the collection time constitutes the business data y i The extended neighborhood set N i ; Based on the extended neighborhood set corresponding to each business data, abnormal business data is determined from multiple business data.

The invention discloses a big data-based foreign trade business data collaborative analysis method and system, and belongs to the technical field of data collaborative analysis management. The method comprises the following steps: monitoring transmission performance data of each department in real time, and dynamically optimizing a data transmission process according to the transmission performance data of each department; monitoring the currently completed task load of each department in real time, and dynamically transmitting the task data according to the currently completed task load of each department and the transmission performance of each department; updating information of each department is monitored in real time, and the task data updating frequency is dynamically adjusted according to the updating information of each department and the transmission performance of the system. According to the method, dynamic optimization of data transmission, intelligent transmission of task data and accurate adjustment of updating frequency are realized by monitoring transmission performance, task completion amount and updating information of each department in real time, so that foreign trade business data processing efficiency is remarkably improved, and reliable data support is provided for foreign trade business.

The application discloses a business data processing method and device, which can be applied to the financial field or other fields. If fault data is generated by a target system, first associated data of the fault data and to-be-handled business of the target system is acquired, second associated data, that is, data related to the to-be-handled business in a virtual system, is acquired. If the first associated data is the same as the second associated data, the priority of the to-be-handled business is determined, and then a virtual system corresponding to the target system is called to control the virtual system to handle the to-be-handled business based on the priority. If the first associated data is not the same as the second associated data, the target system is controlled to handle the to-be-handled business. In this way, when the system fails, the priority of the to-be-handled business and whether the to-be-handled business is related to the fault data are judged, and then the to-be-handled business is handled, so that the efficiency of handling the business by a user is improved.

The invention provides a business data processing method and electronic equipment. The method comprises the steps of obtaining business flow data from a plurality of data sources and performing structured processing to obtain structured flow data, obtaining reference data, determining a business checking process according to the type of a target business, the business checking process comprising a plurality of business checking nodes, and each service checking node executes service checking processing in parallel based on the structured pipeline data and the reference data to obtain checking results of multiple dimensions, and service checking information is obtained according to the checking results of the multiple dimensions. Multi-source heterogeneous data acquisition is realized through the RPA robot, data structured processing is performed by using a large language model, a service checking process pre-configured by a user is dynamically called according to a service type, and checking processing is executed in parallel by a plurality of service checking nodes in multiple dimensions, so that the service checking efficiency is improved. And the business requirements of complicated data sources, variable formats, large check quantity and high accuracy requirements in finance and other scenes are effectively met.

The invention relates to the technical field of manufacturing data processing, and discloses a production business data processing system for a discrete manufacturing workshop, which comprises an asynchronous data acquisition module for acquiring an asynchronous event pulse sequence of a discrete execution node; the mapping transformation module establishes an addressing mapping relation between an event source and a memory logic bit plane and generates an original differential bitmap; the bitmap filtering module is used for hedging paired logic flipping signals by utilizing an exclusive-OR logic self-reversal principle and filtering jitter interference at the edges of the signals so as to generate a net value difference bit plane; the state synchronization processing module performs in-situ upset updating on the state global bitmap through address offset addressing according to the bit identifier, and through a bitmap differential synchronization mechanism, asynchronous state updating without transaction lock constraint is achieved, calculation blocking generated by high-frequency pulse impact is relieved, and the real-time performance and stability of system data throughput are enhanced.

The application provides a service data processing method, device and equipment under a unit architecture and a medium. In the method, when a database is accessed, the target database identifier generated according to the service data processing message not including the specified database identifier is included in the thread variable library, the target database identifier is taken out from the thread variable library, the database corresponding to the target database identifier is accessed, and service data processing is performed. According to the scheme, when the database is accessed, the target database identifier is obtained from the thread variable library, and then the database corresponding to the target database identifier is accessed, so that the access efficiency of the database is effectively improved, and the processing efficiency of the service data is improved.

The invention relates to a business data processing method and device, equipment, a medium and a program product. The method comprises the following steps: in response to a business data processing request, mapping business data in a preset data source through a data operation layer to obtain mapping data; performing data screening on the mapping data through the global processing layer to obtain first screening data, and performing data cleaning on the first screening data through the global processing layer to obtain first cleaning data; performing data screening on the mapping data through the dimension processing layer to obtain second screening data, and performing data cleaning on the second screening data through the dimension processing layer to obtain second cleaning data; aggregating the first cleaning data and the second cleaning data through the data service layer to obtain first aggregated data; aggregating the first aggregated data and the second cleaned data through the application data layer to obtain second aggregated data; the aggregation strength of the data service layer is lower than that of the application data layer. By adopting the method, the business data processing efficiency can be improved.

This invention belongs to the technical field of program control systems, specifically relating to an EtherCAT master station system based on Qt and a multi-task scheduling method. The system includes a human-computer interaction module, a task scheduling management module, an EtherCAT master station protocol stack function module, an XML slave configuration file parsing module, a network communication module, and a serial communication module. The human-computer interaction module includes real-time business display and control, online debugging of EtherCAT communication data, basic business configuration and modular debugging, and system authentication. The task scheduling management module includes system working status management, complex business data processing, and task scheduling. The EtherCAT master station protocol stack function module includes real-time data processing of the controlled object, business control logic management of the controlled slave station, EtherCAT master station initialization process, and interface implementation of the controlled object's business processing process. This invention significantly improves the development efficiency and system performance of the EtherCAT master station system, meeting the requirements of modern industrial control systems for real-time performance, stability, and user experience.

The invention relates to the field of data retrieval, in particular to a business data space-time label generation method and system based on a space entity. The method has the beneficial effects that the effective label is set for the business data by considering and identifying the anchoring word in the business data, screening the effective anchoring set, determining the anchoring characteristic, calculating the information description effective parameter for the business data based on the anchoring characteristic; and adaptively generating feedback data for different service data based on the validity labels subsequently. When a large amount of service data is processed, the quality of different service data is defective and irregular, and the accuracy of the feedback data is improved by analyzing the validity of the service data and adaptively selecting different strategies for generating the feedback data, so that manual inquiry is reduced, and the availability of the service data is improved.

The application relates to the technical field of visual lane modeling, and discloses a business data processing method and system based on visual lane modeling, wherein a multi-task prediction model of a graph neural network and a Transformer fusion is trained based on multi-source historical business chain data, a plurality of groups of lane layout and event configuration schemes are generated in combination with real-time operations of a user captured by a design interface, the optimal scheme is selected through simulation evaluation and filtering, and visual display is performed, and finally, visual lane modeling is executed according to user feedback, through automatic data processing, high-precision model prediction, real-time interactive optimization and visual modeling, the design efficiency and quality of a business chain are improved, meanwhile, model prediction based on historical data avoids artificial experience deviation, meets the comprehensive requirements of real-time performance, reliability and resource efficiency for complex equipment development, and provides efficient technical support for the landing of model-based system engineering in the field of complex equipment.

The embodiment of the invention discloses a batch service data processing method and related equipment, which are used for avoiding rollback of a whole batch of service data caused by processing failure of a single service entity and improving the batch service data processing efficiency. The method comprises the following steps: acquiring batch service processing requests for a plurality of service entities; constructing a transaction unit for each business entity; packaging a plurality of data operations corresponding to the service entity into a data operation sequence; respectively executing the data operation sequence of each transaction unit on one or more business processing nodes, enabling each data operation to execute local business operation on the corresponding business processing node so as to complete business data change, and recording the execution state of each transaction unit in a transaction log; and according to the execution state of each transaction unit recorded in the transaction log, submitting or rolling back the changed business data of each transaction unit so as to reserve the changed business data in the successfully executed transaction unit and revoke the changed business data in the unsuccessfully executed transaction unit.

The invention belongs to the technical field of business data processing, and particularly discloses an industrial park intelligent investment attraction management system and method based on machine learning, and the method comprises the steps: collecting an enterprise interaction log record, and extracting a feedback response index from the click rate and the stay duration; according to the index quantization professional depth and the initial weight of the data proportion, obtaining an attribute parameter vector; processing the attribute parameter vector by adopting a reinforcement learning algorithm, if a feedback response index exceeds a preset threshold value, improving the association strength of policy preference and case similarity, and obtaining an adjusted parameter vector through iterative updating; analyzing a restriction relationship between abstract description and emotional tendency according to the adjusted parameter vector, if the proportion of the abstract description is higher than a data proportion, reducing the proportion, and fusing chart response elements to determine an optimized content template; the invention aims to solve the problem of poor user interaction feedback and content attraction in the investment attracting content pushing process in the prior art.

The application discloses a kind of deep learning model training sample intelligent labeling method, comprising: if labeling task is not in business system, then outside business system labeling is carried out;If labeling task is in business system, then inside business system labeling is carried out;According to the number of labeling sample obtained by outside business system labeling and inside business system labeling, it is judged whether it needs incremental labeling;If it does not need incremental labeling, then labeling task ends;If it needs incremental labeling, then outside business system labeling is optimized by incremental labeling.The application improves the data labeling efficiency of labeling personnel, and also integrates the business experience and knowledge of labeling personnel into the business data processing process, realizes the "business data processing-feedback-model updating" cyclic iteration, and improves the performance and efficiency of intelligent processing system.

This application relates to a method and system for ensuring data consistency between business systems based on bidirectional synchronization, belonging to the field of business data processing technology. The method includes: receiving incremental data events from at least two business systems and generating a vector label for each incremental data event; performing conflict detection on concurrently processed incremental data events based on the vector labels and outputting a conflict type identifier; selecting a corresponding synchronization channel based on the conflict type identifier and current system operating status parameters; transmitting the incremental data events to the target business system through the selected synchronization channel and monitoring the execution status, triggering a compensation transaction when execution fails; receiving response information returned by the target business system and updating the inter-system data flow topology based on the response information; detecting the existence of data loops based on the data flow topology, and performing loop blocking operations when a data loop is detected. This application can improve the collaborative efficiency and stability of multiple business systems.