170 results about "Business domain" patented technology

The invention discloses an intention classification method and device based on vector retrieval and context awareness and a medium, and relates to the technical field of artificial intelligence. The method comprises the steps of extracting business metadata and associating the business metadata with typical problem examples to generate a standardized service description document; encoding the standardized service description document into a high-dimensional semantic vector through a pre-training language model, and constructing a neighbor search index to store the high-dimensional semantic vector; splicing the user identity information and the current question text into an enhanced query statement, and encoding the enhanced query statement into a context-aware dynamic query vector through a semantic model; performing similarity retrieval based on the dynamic query vector to obtain candidate intelligent services, performing business domain filtering, context weighted sorting and dynamic priority rearrangement, and outputting target recommendation services; by collecting interactive behavior data of a target recommendation service, quality scoring is performed on service descriptions and problem examples based on a preset evaluation rule, and the service descriptions and the problem examples of which the quality scores are lower than a quality threshold value are updated.

The invention discloses a high-performance AIOT real-time data processing method and device based on Flink, Kafka and Dores, and the method comprises the steps: constructing an end-to-end hierarchical architecture, capturing multi-source database change data in real time through Flink CDC, and analyzing semi-structured data in combination with Apache NiFi, and generating a standardized data stream; the method comprises the following steps: realizing message routing based on KafkaTopic division of a service domain, ensuring the consistency of a data structure by using Schema Registry, and optimizing the transmission efficiency through a dynamic compression algorithm; an Flink real-time computing engine is adopted to implement window aggregation, asynchronous dimension table association and incremental state persistence strategies, and the resource fluctuation and state management problems in streaming computing are solved; time pre-partitioning and intelligent cold and hot layering are achieved through a Dores storage layer, the query performance is improved in combination with materialized views and multi-level indexes, and finally a full-link closed loop of collection-transmission-calculation-storage-management is formed. According to the invention, the problems that the real-time performance and the consistency are difficult to balance and the system complexity is high in the prior art are solved.

The invention relates to the technical field of cable laying management, and discloses a power industry cross-domain computing power dynamic scheduling system based on super intelligent fusion. According to the system, computing power demand data of each business domain in the power industry is collected in real time, computing resource demand characteristics in different business scenes are identified, and a cross-domain computing power demand characteristic graph is generated; meanwhile, the real-time load state and the available resource quantity of each computing node are continuously tracked, and a distributed computing power resource state matrix is constructed; analyzing and calculating a matching relationship between resource demands and available resources, and generating a multi-objective optimized computing power scheduling strategy scheme; according to the scheme, power business calculation tasks are distributed to optimal calculation nodes according to priorities and resource requirements, and a cross-domain execution process is triggered; and finally, the task execution state and the resource use condition are monitored in real time, an evaluation report is generated and fed back to a strategy generation module, closed-loop optimization is formed, and efficient collaboration and dynamic scheduling of cross-domain computing power resources in the power industry are achieved.

The invention relates to a method, a system and equipment for generating a large model SQL (Structured Query Language) based on business domain semantic enhancement and multi-round voting. The method comprises the following steps: acquiring a natural language input by a user to recognize and judge a business field related to user query; performing semantic annotation and expansion on the input query; organizing related information into Prompt, inputting the Prompt into a large language model, and generating an SQL statement; generating a plurality of candidate SQL statements, and selecting the candidate SQL statements with the highest occurrence frequency as output; and submitting the finally output SQL statement to an actual database system for execution, and returning and displaying a query result. Through the technologies of business domain division, data structure semantic annotation, multi-round candidate generation, voting screening and the like, SQL generation accuracy and system robustness of natural language query are remarkably improved, query intentions and field constraints in business scenes of enterprises such as banks and the like can be accurately recognized, field matching errors are avoided, and the query efficiency is improved. And through multi-round iterative generation and consistent voting screening, the correctness and stability of the output SQL statement are ensured.

The invention provides a syntactic structure tree-based code change influence intelligent analysis method and system, and the method comprises the steps: extracting a control flow, a data flow and a call flow according to an AST generated through the analysis of an original code and a changed code, and constructing a static dependency graph SDG containing a multi-dimensional dependency relationship; the method comprises the steps that a base layer is used for comparing AST differences before and after code change and generating grammatical structure change feature vectors; the service layer matches a corresponding service label for the changed AST node by using the service domain template; the change labeling layer constructs a cross-version dependency chain for the change AST nodes and generates historical feature vectors; and calculating a risk value of changing the AST node by utilizing a feature calculation result and combining with a multi-dimensional influence diffusion algorithm, and automatically generating a decision suggestion. According to the method, multiple dimensions of a control flow, a data flow and a call flow are deepened, risk prediction is optimized by utilizing natural language processing and historical change data, and the influence brought by code change is assisted to be better understood and managed.

The invention provides a business modeling method, medium and system based on an enterprise data asset management platform, and belongs to the technical field of modeling methods.The business modeling method based on the enterprise data asset management platform comprises the following steps that an enterprise data asset catalog is read to generate a data asset list, the method comprises the steps of extracting a foreign key association relationship between data tables to construct an initial entity relationship table, calculating reference frequencies between the data tables to generate an entity association degree matrix, dividing a service domain by adopting a K-means clustering algorithm, counting data table fields in the service domain to generate a data table field mapping table, recording a data table operation sequence to construct a data table operation link diagram, and establishing a data table operation link diagram. The method comprises the following steps: generating a data table node evaluation matrix, dividing sub-domains and determining a core entity, and constructing and training a multilayer neural network model for constructing business affiliation, data table incidence relation and business interface definition of a new data table, so as to solve the defects in the aspects of data asset relation discovery, business modeling automation, service interface generation and the like in the prior art.

The invention discloses an operation data processing method and system based on a compliance verification library and a risk control plan, and belongs to the technical field of data compliance and risk control, and the method comprises the steps: obtaining an execution plan of a target operation task and risk control strategy information of the execution plan, analyzing operation data items, distributing corresponding compliance verification time windows and levels, and forming an operation data verification scheduling table; according to the verification level and the business domain, a rule set is extracted from a compliance verification library, and rules comprise predefined rules, model output rules and historical violation rules; field-level matching, logic consistency verification and cross-source linkage verification are executed in the verification time window; when the verification result meets the triggering condition, generating an abnormal event, and executing response operations such as delay, recheck or interception; and finally, writing the execution state and the verification result into an abnormal log queue for risk control strategy parameter updating or re-evaluation. According to the method, the dynamic compliance verification and strategy closed-loop optimization of the operation data are realized, and the intelligent compliance control capability of the system is improved.

The invention discloses a block chain cross-domain service method and system based on sharing verification and a smart contract, and the method comprises the steps: building a cross-domain sharing channel between a first business domain of a first block chain and a second business domain of a second block chain through a main node on a relay chain; performing hash operation on the original data to obtain a data fingerprint, packaging the data fingerprint, the data metadata and the digital signature of the data holding node into a first message, and submitting the first message to a relay chain through a sharing channel; after receiving the first message, performing consensus verification on the data fingerprint based on a threshold signature mechanism, and writing a verification result into a shared state table; querying the verification state of the data fingerprint from the sharing state table through the data use node in the second service domain, and requesting to download the encrypted data from the intelligent contract of the relay chain; executing permission judgment, and triggering a key distribution contract to transmit a decryption key to a data use node; and downloading the encrypted data, and writing the cross-domain data sharing transaction record into a block chain account book of the second business domain.

The invention discloses a row-level data permission authorization method and device, equipment and a medium, and relates to the technical field of computers. Comprising the following steps: registering basic data into a preset database; configuring a corresponding field management user with a field management authority for the preset service field; creating or updating a record in a user data permission table based on the user permission application to determine a permission relationship between the user identifier and the entity data; registering a service data table and a mapping relation between an entity column and an entity type in the service data table in a preset service field based on a user instruction of a field management user; and dynamically generating a permission filtering condition based on the query SQL and the user identifier so as to generate an SQL statement with permission filtering, and querying corresponding service data from the service data table based on the mapping relationship so as to generate a corresponding query result based on the service data. Therefore, the efficiency and flexibility of line-level data permission authorization can be improved on the premise of ensuring data security.

The invention relates to the technical field of digitization, in particular to a digitization transformation project operation system and method.The digitization transformation project operation system comprises a data intelligent core layer, an elastic infrastructure layer, a man-machine cooperation layer, a safety compliance layer and a value operation layer, and the data intelligent core layer is used for achieving cross-business-domain data management and AI model full-life-cycle management; the data credibility and the model practicability are ensured; according to the method, the defects of cross-service domain data rights and responsibilities disorder and insufficient sensitive information protection due to adoption of a centralized architecture in traditional data governance, and resource waste caused by AI model development and operation and maintenance splitting are overcome; according to the scheme, the service domain sovereignty is divided through the distributed data governance framework, the field-level authority control is realized in combination with the dynamic desensitization technology, and the AI model full-life-cycle management platform is established, so that efficient collaboration of cross-domain data and automatic recovery of model resources are realized, the data credibility and the model practicability are remarkably improved, and the risk of data abuse is reduced.

The invention belongs to the technical field related to data processing, and particularly relates to a data authority evaluation method under a multi-source social governance data fusion scene, which comprises the following steps: extracting metadata of to-be-evaluated data; inputting the metadata into the fine-tuned large model to obtain a matching score of the to-be-evaluated data and all preset social governance business fields, a professional authority score of a to-be-evaluated data source department or institution and weights of representation form standardization degree evaluation, data field association degree evaluation and data source department level evaluation; calculating a data field association degree evaluation score based on the matching scores of the to-be-evaluated data and all preset social governance business fields; determining a data source department level evaluation score based on the professional authority score; calculating a representation form standardization degree evaluation score by comparing the to-be-evaluated data with an industry data specification; and weighting each score to obtain an authority quantitative evaluation score. According to the invention, authority of multi-source social governance fusion data can be guaranteed.

The invention provides a multi-agent system and a multi-agent dialogue management method. The system comprises a main agent, a dialogue management module and a plurality of sub-agents, and the sub-agents correspond to processing of tasks in different business fields respectively; the main agent is used for calling the dialogue management module under the condition that a user request is received; the dialogue management module is used for acquiring historical information corresponding to the user request, analyzing the historical information and returning an analysis result to the main agent; the main agent is further used for determining corresponding request task data and a target sub-agent in the multiple sub-agents according to the analysis result and the user request, and sending the request task data to the target sub-agent; the sub-agent is used for processing based on the request task data, obtaining a task processing result and returning the task processing result to the main agent; and the main agent is also used for returning a corresponding natural language reply to the user according to the task processing result of the sub-agent.

The invention discloses a business data index full life cycle treatment method and system based on a knowledge graph. The method comprises the following steps: constructing a dynamic knowledge graph which takes a business index, a derivative index, a data source, a business domain and an authentication process as entities and takes a blood relationship, a dependency relationship and an approval state as edges; the approval state is mapped into a map edge attribute in real time, and map updating is automatically triggered after approval is passed; analyzing the spoken language query through a natural language processing engine and returning a visual result with an interpretation path; a streaming processing engine is adopted to complete increment synchronization of downstream derivative indexes within five seconds after the index calibers are changed; the system is composed of a graph construction module, a process synchronization module, an NLP query module, a real-time synchronization module and a privacy protection module, and can be operated on general electronic equipment or a storage medium. The method has the advantages of real-time closed loop, zero-threshold interaction and verifiable privacy protection, and is suitable for data governance scenes in the fields of finance, e-commerce and the like.

The invention discloses a flow chart construction method, electronic equipment, a storage medium and a computer program product, relates to the technical field of flow chart design, is applied to a to-be-constructed flow chart, and comprises the following steps: searching business domain knowledge associated with flow information in a preset knowledge base according to the received flow information, the flow information comprises a target flow chart node selected by the user in the to-be-constructed flow chart; determining a large model cue through the process information and the business domain knowledge, and inputting the large model cue into a preset large model to obtain a node recommendation list; and outputting a node recommendation list, and associating the flow chart node selected by the user in the node recommendation list with the target flow chart node. The technical problems of low flow chart construction efficiency and poor effect are solved.

The invention provides a domain-oriented block chain intelligent contract generation method and system, and relates to the technical field of block chains, and the method comprises the steps: guiding a user to completely express a business demand through a multi-round question and answer mode, and generating a business flow chart; constructing an interactive flow chart editing interface to optimize a business flow chart; establishing a large language model for generating an intelligent contract code; constructing a Prompt engineering framework and a domain knowledge base for the business domain, retrieving related knowledge from the domain knowledge base, inputting a large language model for generating an intelligent contract code, and generating the intelligent contract code; and performing security check on the smart contract code, deploying the smart contract code to a target block chain platform, and displaying the execution state of the smart contract and the actual operation effect of the smart contract in real time. According to the method, non-technical personnel can directly express business requirements through intelligent dialogue guidance, the development efficiency is greatly improved, and the whole process of automatic requirement collection, flow chart generation and code generation is achieved.

The invention discloses a business domain division method and device for a database table, a medium and a product, and relates to the technical field of data processing. According to the scheme, when the business domain grouping requirement of the database table exists, from the three aspects of the structure, the semantics and the behavior of the database table, the similarity degree of three dimensions including the foreign key relation, the name similarity and the common current mode between the database tables is comprehensively considered; the problem that effective information in metadata is difficult to extract due to the fact that only an NLP model is used for unilaterally extracting database table information in a traditional method is effectively avoided; and finally, determining a corresponding comprehensive weight by utilizing the structure weight, the semantic weight and the behavior weight corresponding to each database table, namely dividing each database table into a plurality of business domain groups according to each comprehensive weight, so that manual intervention can be effectively reduced, and the method is suitable for a large-scale database scene.

The invention relates to the technical field of block chain technology and education data management, and discloses an education data management system and method based on a block chain, and the method comprises the steps: constructing an education business field specific language, and training an education business intention understanding model; applying a constraint solving algorithm to solve the smart contract parameters meeting various constraint conditions, and generating a smart contract code meeting multi-objective optimization; performing multi-level formalized verification on the generated intelligent contract code; constructing an educational policy and regulation knowledge base and calculating a contract policy compliance score; implementing a hierarchical transition strategy; the system is constructed based on a domestic Feiteng processor and a Kylin operating system, and stable operation and data security in an extreme environment are ensured; the technical problems of difficulty in intelligent contract development, difficulty in policy compliance evaluation and complexity in contract evolution upgrading in education data management are solved, and reliable storage, safe sharing and effective management of education data are realized.

The application discloses a tax intelligent operation and maintenance management system based on a digital and intelligent base, and particularly relates to the technical field of tax business operation and maintenance; the system is constructed by collecting tax operation and maintenance related data of a sharing platform, a tax and bank channel and internal multi-business domains, constructing a cross-domain operation and maintenance object correlation graph, and identifying the relationship change of version solidification and adjacent version difference recognition caliber coding parameter data based on the graph; the system compares and matches to identify the drift candidate set of the cross-domain operation and maintenance object correlation edge, performs the presequence constraint and postsequence landing point check along the caliber coding parameter mapping transmission path to form an influence fragment set, and extracts a semantic abnormal fragment set through semantic consistency review of running representation data; finally, the relationship drift source object is determined according to the co-occurrence convergence characteristics of the relationship change item, so that the accurate identification and rapid positioning of the tax business semantic level anomaly are realized.

The invention provides an automatic component positioning method and device for an MOM service domain, equipment and a medium, and relates to the technical field of computers.The method comprises the steps that in response to dragging operation of a user on a specified component, intention distances between a plurality of static components on canvas and the specified component are calculated; calculating a positioning edge direction matching degree between the plurality of static components and the specified component; calculating the overlapping degree between the plurality of static components and the specified component; performing normalized weighted summation on the intention distance, the positioning edge direction matching degree and the overlapping degree, and determining the component with the highest score as a target component; determining a target anchor point according to the target component; and generating a visual shadow at the target anchor point, and when the specified component is dragged into a preset range of the shadow, automatically aligning the central point of the specified component to the target anchor point and updating the coordinate. Through calculation of the sum of the intention distance, the positioning edge direction matching degree and the overlapping degree, it can be ensured that the components are accurately aligned on the canvas, and overlapping is avoided.

The present invention relates to the field of electronic technology, and discloses a watershed knowledge sharing method, device, computer equipment and medium. The method of the present invention calculates the knowledge evaluation value of the corresponding watershed business process through the cost information, first ranking coefficient, second ranking coefficient and business relevance index of each business process in different business domains, realizes the knowledge value evaluation of the relevant information of each business process, and performs subsequent watershed business knowledge sharing based on the knowledge evaluation value. Watershed knowledge sharing is realized based on the value of watershed business process information, and watershed business knowledge of different values ​​is shared with users who meet the corresponding requirements, thereby solving the knowledge isolation problem caused by different structures within the organization and improving the knowledge sharing ability of enterprises with different organizational structures but in the same field.

The invention discloses an aeronautical manufacturing enterprise-oriented multi-dimensional business index management system, which comprises a data source management module for managing data source information required by the multi-dimensional business index management system and executing data source connection and data acquisition; the business domain management module is used for setting business domains, business classifications, index sources and index classification information of to-be-managed indexes; the calculation dimension management module is used for maintaining and performing mutual exclusion group management on each calculation dimension; the index calculation model configuration module is used for configuring a business domain, business classification, an index source, index classification, calculation parameters, a calculation formula, calculation frequency and calculation dimension of an index to be maintained; and the automatic calculation module is used for calculating an index result according to the content configured by the index calculation model configuration module and the calculation frequency. According to the method, the problems of complex flow, large workload, extremely low index calculation and utilization efficiency and the like of the existing calculation mode of the business indexes in the aeronautical manufacturing enterprise are solved.

The application relates to the technical field of blockchains, and discloses a mobile product whole-life-cycle tracing method based on a blockchain, which comprises the following steps: a relay chain extracts compliance judgment indexes in administrative rule update data, generates compliance check salt values in combination with time stamps, and distributes the compliance check salt values to parallel chains of each business domain; the parallel chains of the business domain map material tracing data and the compliance check salt values, generate business state vectors containing local details and embedding time-effect features of the compliance judgment indexes; and the relay chain implements logical check on the collected business state vectors by using an orthogonal state mask, anchors to a global tracing ledger after verifying a compliance time sequence, and establishes a strong time sequence constraint benchmark of management logic in a heterogeneous chain by the compliance check salt values, eliminates compliance risks caused by rule replacement lag of local nodes, and ensures response efficiency of cross-chain tracing under a mass transaction condition by using a bit operation mechanism.

The application discloses a domain-specific language design method, device, equipment and storage medium. The method comprises the following steps: determining a syntax rule corresponding to a target domain according to a business logic of the target domain; writing the syntax rule according to a regular expression to obtain a target syntax described based on the regular expression; and generating a program package under a target running environment based on the target syntax, so as to develop the business logic by using the program package. The syntax rule is written by using the regular syntax, is not limited by a predefined syntax, and can be customized according to any business domain. Meanwhile, the running program under any environment can be output by specifying the target running environment, so that the generated program package can run in any specified environment, and the flexibility of the domain-specific language design is improved.

The application relates to the technical field of question precision, and discloses a financial intelligent question precision method based on dynamic calculation optimization, which comprises the following steps: obtaining financial question information, rewriting the financial semantics through a double knowledge base, standardizing the time of multidimensional rules, and obtaining standardized text by simultaneously performing text clarification; constructing a data access gateway, partitioning according to a business domain and a time granularity, and performing data quality optimization processing; constructing a financial index dynamic rule base, intelligently adapting, and generating visual rules; setting a double-trigger updating mechanism; performing entity labeling processing, calculating entity probability, establishing the correlation between entities, disassembling a composite inquiry into independent subtasks, and performing sorting; constructing a calculation engine, calculating index results, analyzing total execution time, performing three-way verification by comparing a preset financial reasonable interval, judging the effectiveness of the index results, summarizing core information, and structurally displaying and concluding.

The application provides a productivity middle platform micro-service granularity determination method, medium and system, and belongs to the technical field of electric digital data processing. Firstly, stable load indexes and fluctuation load indexes are obtained through productivity middle platform runtime parameter collection and multidimensional decomposition. Then, a business domain interaction matrix is constructed and singular value decomposition is performed to generate an initial micro-service division scheme. Next, an evaluation equation set containing data consistency, interface calling, business cohesion and service dependency is established. On this basis, a dependency complexity coefficient matrix is constructed, and an L-shaped domino covering algorithm is used to determine a service merging scheme. Finally, the system complexity is predicted through a service evaluation neural network model, and a genetic algorithm is used for iterative optimization until the optimal micro-service granularity scheme is obtained, thereby solving the technical problem that the productivity middle platform micro-service granularity cannot be dynamically and adaptively adjusted in the prior art.

The present application relates to the technical field of artificial intelligence large model, specifically to a report generation agent autonomous construction method based on knowledge enhanced large model, which comprises: knowledge extraction on business domain structured documents and unstructured texts and construction of domain knowledge graph, adoption of an improved progressive knowledge injection algorithm to integrate knowledge into general large language model parameters to form a knowledge enhanced base model. Extraction of task planning sequences and operation trajectories generated by historical reports to construct a demonstration sample library, and fine tuning of a primary report generation agent through a behavior cloning strategy. A reinforcement learning training field containing multiple rounds of complex tasks and diversified environmental disturbances is built, interactive data is collected to form a behavior experience pool, decision parameters are iteratively updated based on proximal policy optimization, and autonomous construction of the agent is completed. This method can improve the effect of domain knowledge fusion and enhance the task planning and autonomous decision-making ability of the agent in complex scenarios.

The application belongs to the technical field of sensitive data management and control, and particularly relates to a business sensitive data management and control system based on a block chain, wherein the system comprises an architecture definition module, a ledger segmentation design module, a sub-ledger consensus construction module, a cross-business domain data interaction module, a sensitive data node allocation module and a ledger fault tolerance module. The scheme realizes local encrypted storage of sensitive data original text and operation logs of the sub-ledger by constructing a double-layer segmented architecture of the main ledger and the sub-ledger, combining cloud network fusion technology, completing sensitivity evaluation through feature selection and a machine learning model, preferentially allocating high-frequency data to near-main-ledger nodes according to data heat, preferentially allocating new data to low-load nodes according to node load, obtaining an optimal node load allocation scheme through a genetic algorithm when there is no low-load node, realizing dynamic expansion and merging of the sub-ledger, reducing data migration cost during business domain expansion, and guaranteeing uninterrupted sensitive data access services.

The embodiment of the invention discloses a data processing method, device and equipment. The method comprises the following steps: receiving a model updating request for a service processing model; in response to the model updating request, obtaining training data corresponding to a business field to which the business processing model belongs; training the business processing model based on the training data, and judging whether the business processing model obtained by training meets a model training requirement or not; under the condition that it is determined that the business processing model obtained through training does not meet the model training requirement, target modal data meeting a preset complementary relation with the training data is screened out from other modal data according to the data dependency relation between the training data and the other modal data; and on the basis of the target modal data and the training data, continuing to perform model training on the trained business processing model until the business processing model meeting the model training requirement is obtained.

This application relates to the field of security auditing technology, and provides a method and system for cross-domain business behavior auditing based on clock synchronization. The method includes: performing clock calibration and dynamic compensation on slave nodes of each business domain, assigning a unique time sequence identifier to each slave node of the business domain to bind domain attributes and node identity information; encrypting and collecting operation logs and / or data flow records of each business domain to obtain core time sequence features; constructing a benchmark fitting based on the core time sequence features and calculating residuals, quantifying the residuals to obtain time sequence deviation quantization values, and performing cross-domain business abnormal behavior detection based on the time sequence deviation quantization values ​​and multi-level abnormal thresholds; when abnormal behavior is detected, performing time-series full-link tracing based on the calibrated timestamp and unique time sequence identifier, and reliably storing the abnormal behavior and corresponding tracing link data, thereby achieving accurate link reconstruction of abnormal behavior and enhancing the integrity of the evidence chain, and improving the accuracy and reliability of cross-domain business compliance auditing.

The present invention discloses a heterogeneous data fusion indexing method and system based on knowledge graph, comprising the following steps: analyzing entity types and relationship types in heterogeneous graphs, synchronizing and defining entity type data respectively, and defining heterogeneous entity mapping relationships; using graph adaptation to obtain entity and relationship data from two types of heterogeneous graphs respectively, and caching the data such as message middleware; constructing a view domain knowledge graph and a business domain knowledge graph; fusing the constructed view domain knowledge graph and business domain knowledge graph to construct a fusion index subgraph; performing mapping relationship analysis and mining based on the constructed fusion index subgraph to achieve disambiguation and fusion of entities in the original graph; providing a standard and unified relationship query interface for heterogeneous graphs and fusion index subgraphs; this solution constructs a data fusion index subgraph through entity mapping of the two types of knowledge graphs to achieve fusion of heterogeneous data.