369 results about "Business entity" patented technology

The invention relates to a multi-view knowledge graph-driven industrial chain collaborative recommendation method, which comprises the following steps of: constructing knowledge graph views of a plurality of business dimensions through multi-source heterogeneous data, and performing feature decomposition and adaptive feature regulation and control; a multi-head knowledge propagation mechanism fusing a business context is provided, and hierarchical volume accumulation and dynamic path selection are carried out in combination with multi-view representation; through wavelet transform and multi-scale time sequence decomposition, constructing dynamic representation of a business entity in combination with an adaptive scale selection mechanism and an attention mechanism driven by industry characteristics; static and dynamic features are fused by using a gating network, a multi-party matching scoring mechanism based on comprehensive representation is constructed, and multi-party business collaboration and recommendation in an industrial chain are supported. By fusing multi-view knowledge graph construction, dynamic business entity modeling and comparative learning technologies, relevance between business of enterprises is disclosed, business recommendation is generated for related enterprises, and a foundation is laid for business resource allocation in an industrial chain.

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 provides a timestamp-based data change intelligent deduplication and message simplification method and system, and the method comprises the steps: capturing a change event of a database in real time, and generating a change record containing a timestamp; based on a preset timestamp comparison algorithm, performing timestamp analysis and comparison on the multiple change records of the same service entity; the change records are grouped according to the service keys, the latest change records are stored and dynamically updated through a hash table, the latest timestamp data under the same service key are reserved, and intelligent duplicate removal of redundant data is achieved; when the data volume exceeds a preset threshold value, a data fragmentation strategy is triggered, batch data is uniformly segmented into a plurality of subtasks, multi-thread parallel processing of fragmented data is achieved by dynamically allocating thread resources, and processing results are summarized; and carrying out merging processing on the deduplicated changed data, constructing a standardized message body, selecting immediate sending or delayed queue distribution according to a message priority, and controlling a network transmission load through a message batching mechanism.

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 provides a knowledge graph construction method based on a low-code development platform, and belongs to the technical field of knowledge graph construction. The method comprises the following steps: counting and carding metadata and business entity structures in a low-code development platform, and formulating a mapping specification for mapping from a relational database to semantic data; obtaining a target relational database in the configuration file, extracting table data and column data in the target relational database, and converting the table data and the column data into entity class parameters and attribute class parameters in the knowledge graph based on a mapping specification; extracting an unstructured data source related to the target business from the low-code development platform, and converting the unstructured data source into structured data; and associating the structured data with the entity class parameters and the attribute class parameters, and storing the associated data in the knowledge graph. Automatic mapping and storage from the relational database to the knowledge graph are realized, so that the data utilization rate and the business intelligence level are improved.

The invention provides a report loading processing method, system and device in an industrial scene and a medium, and belongs to the technical field of report loading. Data source information associated with a service entity identifier is obtained; establishing a dynamic binding relationship between business entity attributes and data source fields, and generating an index metadata template; acquiring data source information associated with the service entity identifier through a data registration component; establishing a calculation mapping relation between the index field and the data source field; generating a standardized configuration file; persisting the generated standardized configuration file to a database; a three-party incidence relation index among an index instance identifier, a service entity identifier and a data source identifier is established, in actual industrial data processing, even if network faults and other problems occur, it can be guaranteed that configuration files are accurately updated, when service requirements change, calculation rules of corresponding levels can be rapidly positioned and adjusted, and the service requirements are met. And the flexibility and accuracy of data processing are improved.

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.

At least one example describes mechanisms generating real-time AI-driven financial reports and responses from financial data of a business entity. In at least one example, the financial data including transaction details and account information from different sources is received. Based on the financial data, a financial report template is generated including performance indicators (PIs) that are dynamically generated by a first one or more machine-learning (ML) models. A second one or more ML models generates a mapping strategy automatically linking the PIs to relevant financial data. In at least one example, based on the template and the mapping strategy, a financial report is generated including estimated values of the PIs for specified time. The financial report is evaluated by a third one or more ML models that generates, via a graphical user interface (GUI), a response including a description of valuable insights, anomalies, and patterns in a natural language format.

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 embodiment of the invention provides a time sequence prediction method and device for hierarchical services, which are used for predicting a time sequence formed by service volumes of service subjects of a single service on multiple levels, and a single level corresponds to at least one service subject. According to one implementation mode, after historical time sequences in one-to-one correspondence with business subjects in multiple levels are obtained, the historical time sequences can be coded to obtain corresponding coding vectors, then joint probability distribution met by the coding vectors is constructed, and the joint probability distribution is obtained. And further, sampling is carried out on each business main body according to joint probability distribution to obtain a sampling sequence, and each prediction sequence for each business main body is determined. The method can improve the accuracy of the prediction result.

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.

The invention relates to the field of computer application, in particular to a method, a device, equipment and a medium for integrating a heterogeneous business system and a workflow system.The method comprises the steps that business entity modeling is conducted on business receipts of the heterogeneous system, and a business table structure, a field type and a business entity referenced by associated fields are described in a setting form; binding a corresponding heterogeneous service system data query API (Application Program Interface) for the created service entity; performing approval form modeling, binding a mapping relationship between form control display contents and business entity fields, generating an approval form, and mapping business form data in real time by the approval form; performing flow modeling, defining a flow chart and binding a flow event, and calling a heterogeneous service system data query API to write back service form data at the event execution time; and modifying a submission button response event of the business form, and calling an open standard API of the workflow system to initiate an approval process. And flow centralized management and control are realized, approval entrances are unified, and consistent approval experience is provided.

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 discloses a service skipping method, system and device in a mobile terminal application, and relates to the technical field of data processing, and the method comprises the steps: obtaining a language instruction, and obtaining a semantic vector and a context feature vector according to a standard service scene specification and context information; according to the expression type, obtaining a to-be-processed intention through processing; the method comprises the steps of extracting an entity and an action in a to-be-processed intention, associating the entity and the corresponding action with a service module, mapping the service module with a URL-Scheme parameter in a preset URL-Scheme scene specification, positioning to a target service module according to a mapping relationship, and performing action execution according to a service entity and a corresponding service action; and if the mapping relationship does not exist, skipping to a cloud big model integrated in the application for processing, and returning a result to the mobile terminal to complete interaction. Therefore, the user can quickly and intelligently complete the skipping and interaction of the service of the mobile terminal through the voice instruction.

The invention provides a project-customized adaptive data query and display method, system, device and medium, and belongs to the technical field of data query, the method comprises the following steps: determining the business meaning of each business entity in a key field in a form scene, and solidifying the business meaning in ERP (Enterprise Resource Planning) system configuration; carrying out association relation configuration on the key fields according to the requirements of the business entities; the association relationship comprises an association table, an association field and an association condition; configuring a target field which needs to be brought out by each service entity in the form scene; and in response to a service demand, determining an association relationship of the key fields according to a service entity type, constructing a dynamic SQL query statement by using the determined association relationship, obtaining target data, and filling the target data into a target field of the form scene. According to the method, the personalized requirements of different projects or departments are met, the data query and display content is flexibly configured, dynamic configuration adjustment is supported, the method adapts to the change of service requirements, and the secondary development workload is reduced.

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.