271 results about "Business entity" patented technology

The invention discloses a law compliance auditing response method driven by an enterprise knowledge graph, and relates to the technical field of artificial intelligence, and the method comprises the following steps: carrying out semantic analysis on a law and regulation text, constructing a context hierarchical expression model, dividing each law and regulation into a title semantic block, a subject semantic block, a limit semantic block and a constraint semantic block, and generating a hierarchical semantic graph. According to the method, the structured analysis of the regulation provisions is realized by constructing the hierarchical semantic graph, and the regulation provisions are accurately aligned with the business entities in the enterprise knowledge graph, so that the reasonable regulation-enterprise semantic mapping relationship is constructed. And boundary reasoning, confidence scoring, context backtracking and semantic correction are combined to realize intelligent discrimination and correction of the applicability of the regulatory obligations. Models and rules are continuously updated through a feedback optimization learning mechanism, the dynamic adaptive capacity of the system and the accuracy of compliance suggestions are improved, the misjudgment risk is remarkably reduced, and the intelligence and the practical application value of the system are enhanced.

The invention discloses an intelligent data stream processing system based on Flink and an implementation method thereof, and belongs to the technical field of distributed streaming data processing, and the implementation method comprises the following steps: a data source access layer uniformly accesses multi-source data; the entity monitoring layer captures service entity change in a non-intrusive manner based on JPA, generates a standardized message body and asynchronously delivers the standardized message body to double channels; the unified event model layer maps the data into a standardized event and expands the standardized event; the Flink stream processing engine layer is used for complex event processing, state management and window calculation, and supports declarative pipeline definition and dynamic construction; the anomaly detection layer performs multi-dimensional anomaly detection; the distributed task scheduling layer schedules tasks according to a DAG model, and realizes load balancing through hotspot splitting and state transition; and the result storage and visualization layer adopts a cold and hot separation strategy to store data, and provides a dynamic visualization interface. The real-time performance, the consistency and the intelligent level of data processing are remarkably improved, and the development and maintenance cost is reduced.

The invention relates to a low-code visualization optimization method and system for power credential development, and the method comprises the following steps: S1, obtaining data in a credential environment, recognizing the interface difference and performance bottleneck points between components through a compatibility test matrix, and building a standardized adaptive interface specification; s2, obtaining a standardized business object model based on the standardized adaptive interface specification; based on the business object model, defining attributes, relationships and constraint rules of each business entity, and forming a data dictionary and an interface specification special for the electric power field; s3, on the basis of the data dictionary and the interface specification special for the power field, constructing a DSL (field specific language) of power visualization; s4, a dragging type interactive design is adopted, and the visual operation is converted into a DSL configuration file; and S5, automatically converting the DSL configuration into a React or Vue component code through a code generation engine, and carrying out compatibility optimization on the kernel of the creative browser. According to the invention, the power credential development efficiency is effectively improved.

The invention relates to an enterprise multi-dimensional business index analysis data resource optimization method, a medium and equipment, and the method comprises the steps: collecting a multi-dimensional business index analysis request of an enterprise business system, carrying out the mode recognition and feature extraction of the multi-dimensional business index analysis request, and generating business entity features; and inputting the business entity features into the resource allocation model, outputting a priority score and a resource demand prediction result, calculating an optimal resource allocation scheme through an optimization decision model based on the priority score and the resource demand prediction result, and performing automatic resource scheduling according to the optimal resource allocation scheme to generate a business decision instruction. And finally outputting a business decision instruction and a data resource management report. The resource reuse potential among different requests is automatically identified and quantified by adopting a set similarity algorithm, so that the enterprise data resource utilization efficiency is remarkably improved, the redundancy calculation consumption is reduced, and the resource allocation is more reasonable and efficient; manual intervention is reduced, and enterprise data resource management efficiency and response speed are improved.

The present application provides a multi-terminal ecosystem fund allocation management system for an e-commerce enterprise, comprising: acquiring tax jurisdiction information of each business entity, comparing tax policies of different regions, and determining whether there is a difference between the tax policies; if there is a difference between the tax policies, acquiring from financial systems of each business entity fund distribution-related transaction data and tax information, and obtaining a unified-format tax information dataset by means of data cleaning and integration; using an association rule mining technology, finding an association mode between fund allocation and tax processing from the tax information dataset, so as to form a tax association rule library for fund allocation; on the basis of the tax association rule library for fund allocation, constructing a tax benefit evaluation model for fund allocation, and predicting a tax impact of a solution by means of inputting different fund allocation solution parameters.

Systems and methods for resolving entity names combine hybrid search techniques with large language models to improve accuracy in matching business entities. The system includes an index builder that generates and stores both sparse and dense vector embeddings representing entity information. A query component performs hybrid searches using both keyword-based and semantic methods to retrieve entity candidates from the stored embeddings. When high-confidence matches are not found, a virtual entity generator leverages large language models to generate additional entity candidates based on the input data. The system employs a re-ranker to order retrieved candidates based on their relevance to the input query. This approach enables accurate entity resolution even with noisy or incomplete input data by combining traditional search methods with advanced language model capabilities.

A system including a media data optimization engine (MDOE) and a method for automatically creating structured data objects for media content rendered in one or more languages in an electronic document of a business entity are provided. The MDOE identifies non-textual objects including media content rendered in one or more languages in the electronic document and generates textual objects in the corresponding language(s) therefrom. The MDOE transforms the textual objects into structured data objects based on configurable criteria and generates a dynamic index-oriented object for the structured data objects specific to the business entity. The MDOE connects the structured data objects to the dynamic index-oriented object by creating linked data nodes therefrom with the dynamic index-oriented object as a core. The MDOE connects the dynamic index-oriented object with the linked data nodes to the electronic document, thereby facilitating dynamic changes to the electronic document and dynamically optimizing the electronic document.

The invention relates to the technical field of artificial intelligence, can be applied to business scenes such as financial science and technology and medical health, and discloses an interaction intention-driven tool scheduling method, device and equipment and a medium. The method comprises the steps of obtaining to-be-processed interaction data of visual data or text data, executing cross-modal semantic analysis to generate a unified interaction intention, and sending the unified interaction intention to a server; detecting intention association strength between the matching tool and the context state data, selecting a context association mode based on the strength, determining a target dialogue node, scheduling the matching tool to perform sandbox execution to obtain a tool execution result, generating response content, and sending the response content to the server; and selectively updating the to-be-processed interaction data, the unified interaction intention, the response content, the tool execution result, the target dialogue node and the extracted service entity data to context state data. According to the method, the interaction accuracy is improved through cross-modal analysis and a switchable context association mechanism, tool decoupling is achieved in a sandbox execution mode, and the system adaptability and stability are enhanced.

The invention discloses a service entity intelligent prediction system and method oriented to multi-dimensional decision support, and relates to the technical field of service prediction. The system comprises a service multi-source data screening module, a service multi-source data correction module and a service entity dimension index output module. According to the method, data fusion is carried out on the multi-source data of each dimension index, an adaptive data screening strategy is selected according to the data conflict detection condition in the process, and then data range verification is carried out on each to-be-input data determined by the data screening strategy; and determining whether to perform data deviation determination based on the verification result so as to determine whether to execute data correction measures, finally, after data fusion, inputting the determined to-be-input data into the prediction model, and outputting each dimension index after index data range determination and a determination result prompt. The intelligent prediction precision of the service entity is improved, and the problem that the intelligent prediction precision of the service entity is reduced in the prior art is solved.

The invention provides an archive full-text intelligent retrieval method and system based on a knowledge graph and electronic equipment, and relates to the technical field of archive retrieval. Comprising the following steps: acquiring standard file metadata and business data related to the standard file metadata; defining an archive entity type of the standard archive metadata and a business entity type of the business data, defining a relationship between business entities and archive entities, and establishing a relationship rule base; constructing a graph data triple comprising entities and relationships based on the successfully matched archive entities, business entities and relationship types, and further establishing a knowledge graph; analyzing the user input text to obtain a user intention analysis result; and based on the user intention analysis result, matching the nodes in the knowledge graph to obtain the matched nodes and the relationship path, and displaying the matched nodes and the relationship path. According to the method, on the basis of the file metadata, the incidence relation between the file metadata and the business data is analyzed through the predefined rule, and the structured knowledge graph is constructed to achieve intelligent retrieval.

A method of verifying that incoming telephone calls to respective customers originate from a business entity known to the customers that includes: receiving data transmitted from a customer application on a first customer device that notifies of a triggering event occurring; generating a business-side version of the verification code for use in association with the first authentication attempt; generating, by the first customer device, a customer-side version of the verification code for use in association with the first authentication attempt; generating a user interface showing the customer-side version of the verification code; and transmitting the generated business-side version of the verification code to a first agent device for authenticating that the first telephone call originates from a first business entity by enabling a comparison verifying that the customer-side version and the business-side version of the verification code are equal.

The invention discloses an artificial intelligence service consultation method based on big data analysis, and the method comprises the following steps: S1, accessing text, voice, image and time sequence data through a multi-source heterogeneous data pipeline, and associating cross-modal data of the same event through a dynamic alignment module; s2, performing multi-modal feature fusion on the data processed in the step S1 by adopting a cross-modal fusion cognitive engine to generate a unified semantic representation vector; and S3, constructing a space-time dynamic knowledge graph based on the semantic representation vector, and detecting an association path and an abnormal mode between the service entities through a graph neural network. According to the method, dynamic alignment and fusion of cross-modal data can be realized through a multi-source heterogeneous data pipeline, business deep association is mined by using a knowledge graph and a causal inference model, and a closed-loop iteration system from quality evaluation to strategy optimization is constructed in combination with reinforcement learning; the core problems of inaccurate demand understanding, insufficient suggestion reliability, low optimization efficiency and the like in traditional consultation are solved.

The invention discloses a multi-source heterogeneous big data aggregation analysis method based on master data modeling. The method comprises the following steps: modeling main data, defining a relation mode of a business entity and a data entity, and outputting a graph structure storage mode; classifying the service entities, and defining different data entity fusion algorithms for different data entity types by taking the main attributes of the service entities as the identification basis of the data entities; accessing data, and cleaning the accessed data; service entities and data entities are analyzed from the cleaned data based on a data entity fusion algorithm, and a relation theme library is constructed according to the incidence relation between the service entities and the data entities; storing the cleaned data and a relation theme library thereof; and carrying out modeling analysis on the cleaned data by combining the characteristics of the business entity and the relation theme library. According to the method, unified management of multi-source heterogeneous mass data is carried out from a global perspective, the blood relationship of the data is clear, and the authority is controllable.

This invention relates to a method for visually recognising and tracking objects and events in 3D space with high accuracy, reduced computational load and fast setup, using virtual sensors that are designed to ensure high reliability and reduce costs by maximising their potential for accurate object recognition for given visual input data. The main task of a virtual sensor is to provide cost-effective and reliable data and replace the use of humans and / or hardware sensors to detect and recognise objects or events that are important to a given entity, such as an industrial enterprise and various business entities. The solution is well suited for industrial applications, especially for tracking larger objects of known shape or appearance, such as in large industrial halls, warehouses without fixed racking systems, container docks, train docks, car parks, etc. It is particularly suitable for tracking coils, metal pieces and larger building components. The method provides a reliable source of i data for obtaining a digital twin of the monitored objects, which represents real-time information about each stock keeping unit (SKU) in the warehouse (WH), bringing significant benefits to WH managers and thus saving human labour spent on searching for materials, improving management flow, reducing overall equipment effectiveness (OEE) of vehicles, improving throughput, quality, etc.

The invention provides a business resource optimization management method and system based on computing power demand prediction, and the method comprises the steps: collecting multi-source heterogeneous data in real time, so as to construct and continuously update a topological graph which represents the dynamic association relationship among a business entity, a logic service entity and a physical resource entity; a time sequence state of a topological graph is input into a prediction model fusing a graph structure and continuous time modeling, multi-dimensional evolution calculation of a node state is carried out by the prediction model, a dynamic resource value signal is generated by a central scheduler under a hierarchical decision framework, a plurality of service unit intelligent agents are guided to carry out distributed collaborative decision, and a multi-dimensional resource value signal is generated by the central scheduler. Iteratively generating an optimal resource allocation scheme; and before the optimal resource allocation scheme is executed, potential risk assessment and credible automatic execution are carried out. Therefore, in a complex dynamic commercial environment, the computing power resource is converted from global perception, accurate prediction and intelligent optimization to risk-controllable closed-loop management and adaptive configuration.

To provide a technique capable of grasping a greenhouse gas emissions status.SOLUTION: An information processing system comprises: a storage unit which stores location information of a plurality of business entities constituting a group; an application form registration unit which allows the registration of an application form for inputting information related to an environment; an item setting unit which allows the setting of prescribed items of the application form; and an application unit which allows the application of information related to the environment across the plurality of business entities. The prescribed items can be set by one business entity among the plurality of business entities, but cannot be set by the other business entity among the plurality of business entities.SELECTED DRAWING: Figure 85

In certain aspects of the disclosure, a computer-implemented method includes creating a wallet for asset tokens and creating an account for a first user upon completion of user onboarding validation. The method includes associating the account with one of an individual and a business entity. The method includes initiating one of know-your-customer (KYC) for the individual and know-your-business (KYB) for the business entity. The method includes enabling the first user to access and make transactions using the wallet.

In an identity governance system, processes enable secure delegation of authority to create and manage identities for users of a computer network and to provision access entitlements to users to network resources in a manner that ensures compliance with security and access policies. The provisioning of access entitlements to users is controlled based on a model of relationships between business entities that the computer network serves. Identities of users are assigned to a node of the model. Provisioning of entitlements for coarse and fine-grain access is restricted based on this assignment. The node of the business relationship model limits the scope of what user access entitlements can be assigned, to whom they may be assigned, and who may assign them.

The embodiment of the invention discloses a finance and taxation service request processing method and device, and the method comprises the following steps: receiving a finance and taxation service request, carrying out the semantic analysis through a BERT model trained based on a finance and taxation field corpus, and extracting a user intention and a key service entity; based on a finite-state machine model, managing a dialogue flow of a business scene, triggering state transition according to a current dialogue state, a user intention and a key business entity, and orderly promoting an invoicing, checking or diagnosing business process; scheduling a corresponding AI capability module to execute a task according to the user intention and a service scene defined by the key service entity; an execution result of the AI capability module is fed back to a front end in real time through a server pushing technology and is displayed in linkage with information input by a user; based on key business entities and operation combinations recorded in a user operation log, the key business entities and the operation combinations are automatically abstracted and packaged into independent reusable functional components. According to the embodiment of the invention, finance and tax business requirements can be adapted through multi-step and scenarized dialogue response.

The invention relates to the technical field of complex equipment data management, in particular to a model-driven complex equipment data relation automatic construction method and system. The method comprises the following steps: constructing a business entity meta-model standard framework comprising a base layer and a domain extension layer through a meta-model technology, and establishing a dual-check system; a hierarchical modeling method is adopted to construct a data model system, and model management is performed through a multi-source heterogeneous data reference mechanism and semantic version control; constructing a data association relationship by adopting a multi-modal fusion method and integrating structural analysis and semantic reasoning; and finally, four-dimensional quality evaluation of integrity, consistency, timeliness and accuracy is carried out on the data association relationship. According to the method, the problems of non-uniform data standards, low association efficiency and incomplete change transmission in complex equipment development are solved, and an automatic closed loop from data association construction to quality control is realized.

The invention discloses a business process construction method and system based on a process engine, belongs to the technical field of business process automation, and aims to solve the technical problem of how to realize intelligent generation, dynamic adjustment and one-key deployment of a business process. Comprising the steps of performing semantic analysis on a demand document uploaded by a user based on an AI large model, generating a process framework based on a key business entity, a business rule and a process node, and outputting a process definition file; based on a natural language interaction mechanism, calling the large model to perform semantic analysis on a natural language instruction input by a user, and correcting the process framework based on an analysis result; integrating the corrected process definition file to a process engine, and performing automatic verification and simulation operation on a process framework; and realizing version management, containerized packaging and one-key release of the process based on an automatic deployment assembly line.

The invention provides a management method and system based on multi-source heterogeneous data, relates to the field of data management, and solves the technical problem that an existing multi-source heterogeneous data management method is low in efficiency. The method comprises the following steps: receiving data streams from different systems through a message bus; performing standardization processing on the field structure of each data stream according to a unified service entity standard to obtain multi-source standardized data, and generating a relation graph based on the multi-source standardized data; based on a preset rule base and a relation graph, performing quality verification and correction on the multi-source standardized data; and writing the verified data into an object storage layer and a real-time query layer according to business theme partitions. The method is used for the whole process of centralized convergence, standardized processing, hierarchical storage, query service and the like of enterprise multi-source heterogeneous data, and an efficient solution is provided for breaking data islands, improving data quality and supporting business decisions.

The invention provides an electric power communication SDH network operation state real-time monitoring system and method, and the system comprises a multi-protocol adaptive collection module which carries out the collection of network element information, performance information, alarm information and equipment information of an electric power communication SDH network according to a preset strategy, performing standardization processing on the acquired multi-source heterogeneous data through a protocol analysis engine module to obtain structured data; the intelligent data screening and deconstruction module is used for analyzing, associating and identifying the structured data to obtain a key business entity; the lightweight packaging module is used for carrying out serialization and compression optimization on the key business entities to obtain lightweight packaging data; and the rendering module is used for carrying out real-time rendering on the basis of the lightweight packaging data to obtain a real-time visual operation state of the electric power communication SDH network. According to the invention, the acquisition efficiency is optimized, real-time monitoring is supported, the bandwidth cost is reduced, invalid data transmission is reduced by 80%, and the fault positioning time is compressed from an hour level to a minute level.

The objective is to provide technology that can understand the status of greenhouse gas emissions. [Solution] An information processing system comprising: a storage unit that stores location information of multiple business entities constituting a group; an application form registration unit that registers application forms into which Scope 1 information, Scope 2 information, and Scope 3 information can be input; and an application unit that allows applications for Scope 1 information, Scope 2 information, and Scope 3 information across multiple business entities, wherein the application unit allows applications for a first application relating to Scope 1 information and Scope 2 information and a second application relating to Scope 3 information to be submitted at different times.

The invention relates to the technical field of business system monitoring, and provides a business system health state intelligent analysis method and system, and the method comprises the steps: obtaining business node data, application performance data and log data, and marking an associated business serial number; associating the service node data, the application performance data and the log data into an event record in the time window by taking the service serial number as an association key; the event records are periodically synchronized into the data warehouse, the incidence relation between the service entities and the technical components is recognized for data in the data warehouse, a relation chain is obtained, and the graph database is updated; and based on the business node data, the application performance data and the log data, performing anomaly detection through an intelligent analysis model to obtain business problems and technical faults, and combining a graph database and utilizing a causal inference algorithm to obtain a causal relationship between the business problems and the technical faults. And causal relationship positioning of business problems and technical faults is realized.

The invention discloses an aviation order analysis method and device, electronic equipment and a storage medium, and relates to the technical field of aviation information or other related fields, and the method comprises the steps: receiving to-be-analyzed target order data, and verifying the target order data based on a preset verification strategy; under the condition that verification is passed, service entity information is extracted from the target order data based on a preset extraction strategy, and the preset extraction strategy is used for specifying an extraction field and a field association relationship; a time sequence correlation model of the target order is constructed based on the business entity information by adopting a time sequence analysis algorithm, and the time sequence correlation model is used for recording all historical business operations of the target order according to a time sequence; and converting the time sequence correlation model into a business flow chart, and rendering the business flow chart to a display area. According to the invention, the technical problem of low data analysis precision caused by poor process data integration capability of an aviation system for complex orders in the prior art is solved.

The invention relates to the technical field of business process modeling, in particular to a meta-model-driven interactive business process intelligent modeling method and system. The method comprises the following steps: constructing a meta-model framework containing core elements such as activities, events and gateways, and establishing a meta-model constraint rule base to define a structure legality rule of a BPMN2.0 specification; based on a domain ontology Schema and the domain exclusive large language model after instruction fine tuning, extracting a business entity and a process relationship thereof from the unstructured text; carrying out information integrity verification and logic consistency detection on the extracted BPMN elements by utilizing a constraint satisfaction algorithm and Petri net reachability analysis; displaying a difference label of the process sketch through an interactive verification interface, and realizing semantic correction and model iteration of a user on the process elements based on a natural language feedback mechanism; an XML code is generated by adopting a template-driven code generation strategy, and a flow chart is generated through a BPMN parser. According to the method, the business process modeling efficiency can be remarkably improved, and the manual intervention proportion in the modeling process is reduced.

The present invention discloses a method, system, and device for redirecting services within a mobile application, relating to the field of data processing technology. The method comprises the following steps: obtaining a language instruction, obtaining a semantic vector and a context feature vector based on a standard business scenario specification and context information; obtaining an intent to be processed based on the expression type; extracting entities and actions in the intent to be processed, associating the entities and corresponding actions with business modules, mapping the business modules to URL-Scheme parameters in a preset URL-Scheme scenario specification, locating the target business module based on the mapping relationship, and executing the action based on the business entity and the corresponding business action; if no mapping relationship exists, redirecting to a large cloud model integrated within the application for processing, and returning the result to the mobile terminal to complete the interaction. The method enables users to quickly and intelligently complete redirection and interaction of mobile services through voice instructions.

The invention relates to an electric power marketing auxiliary work order processing method and system based on a large language model, belongs to the technical field of electric power marketing work order information processing, and is used for solving the problems that unified structured representation and semantic association are lacked and a feedback optimization closed loop is lacked in the prior art. The method comprises the following steps: constructing an interface knowledge graph, collecting and analyzing multi-source interface information and extracting a business entity relationship; analyzing user input based on the pre-training language model, identifying an intention and generating a multi-level dynamic task plan; interface parameters are generated through mapping of the knowledge graph, and safe and reliable interface calling and execution result verification feedback are achieved. By means of the method, unified structured representation and semantic association are achieved, and an optimization closed loop is fed back.

In certain aspects of the disclosure, a computer-implemented method includes creating a wallet for asset tokens and creating an account for a first user upon completion of user onboarding validation. The method includes associating the account with one of an individual and a business entity. The method includes initiating one of know-your-customer (KYC) for the individual and know-your-business (KYB) for the business entity. The method includes enabling the first user to access and make transactions using the wallet.