37 results about "Schema mapping" patented technology

Systems, computer program products, and methods are described herein for generating and mapping unicode for cross-distributed network data transmissions. The present disclosure is configured to identify a cross-distributed network data transmission comprising source ledger code; generate a core schema for a destination ledger, wherein the destination ledger is based on data of the cross-distributed network data transmission; generate, by a ledger transformation module, a data dictionary, wherein the ledger transformation module receives ledger code from a large language model (LLM); generate code mapping instructions for the cross-distributed network data transmission based on the core schema for the destination ledger; convert the source ledger code to a unicode; receive, by a receiver schema mapping module, the unicode and the code mapping instructions; and generate, by the receiver schema mapping module, an intermediary ledger comprising the unicode and based on the code mapping instructions.

A computer-aided design metadata extraction system for automated uploads to a document management system, wherein the system includes the following: a central processing unit configured to control all metadata extraction operations and coordinate the interaction between multiple hardware subsystems; a metadata interpretation controller connected to the central processing unit, which includes a dedicated analysis circuit configured to read file headers, attribute tables, revision identifiers and embedded descriptors from a CAD file; a structured data formatter coupled with the metadata interpretation controller, wherein the structured data formatter is configured to convert the extracted metadata into a normalized schema compatible with predefined fields of a document management system; a volatile memory module and a non-volatile memory module, each coupled to the central processing unit, wherein the volatile memory module is configured to store runtime processing states and the non-volatile memory module is configured to retain persistent logs of extracted metadata and completed upload transactions; a secure communication module comprising an encryption controller and an authentication controller, wherein the secure communication module is configured to transmit the structured metadata and the associated CAD file to the document management system via an authenticated and encrypted connection; and an operator interface comprising a graphical display unit and physical input controls, wherein the operator interface is configured to allow an operator to preview the extracted metadata, configure schema mapping rules, and initiate or approve metadata upload operations.

This invention provides a high-end scientific instrument reliability analysis and design method based on SysML, belonging to the field of instrument reliability analysis technology. The method includes: constructing a system model of the target instrument using SysML, the system model including a requirements diagram, internal block diagram, and attribute library; extracting all failure modes from all failure mode libraries and assigning them global numbers to establish a failure mode mapping matrix; performing failure mode and impact analysis (FMEA) for the target instrument based on the system model to obtain a failure mode and impact analysis table; establishing a parameterized reliability model for each functional path; calculating the reliability constraints of each functional path based on the system model and the impact analysis table; and performing reliability analysis based on the measured attributes and reliability constraints of sub-components to generate an optimization scheme. The advantages of this invention are improved accuracy, consistency, and automation of reliability analysis.

A system and method of use resolves the frustration of repeated manual work during schema mapping. The system utilizes a transformation graph—a collection of nodes (unified attributes) and edges (transformations) in which source attributes are mapped and transformed. The system further leverages existing mappings and transformations for the purpose of suggesting to a user the optimal paths (i.e., the lowest cost paths) for mapping new sources, which is particularly useful when new sources share similarity with previously mapped sources and require the same transformations. As such, the system also promotes an evolving schema by allowing users to select which unified attributes they want to include in a target schema at any time. The system addresses the technical challenge of finding optimal transformation paths and how to present these to the user for evaluation.

A system and method for evicting a resource from a unified network topology (UNT) of a computing environment, is disclosed. The method includes: generating a representation of a UNT for a network topology of a computing environment, the representation based on a unified data schema, wherein the unified data schema is mapped to a plurality of data schemas, each corresponding to a unique data source; receiving an event record at a first time, the event record including a resource identifier; updating in the UNT a representation corresponding to the resource based on extracted data from the event record at the first time; determining that a time period has lapsed from the first time which is greater than a threshold; detecting that a number of event records which include the resource identifier is less than a threshold value; and removing the representation of the resource from the unified network topology.

The invention provides a log management method and device based on an ORC format of Logstash, equipment and a medium. The method comprises the steps that a Logstash service is started, and an ORC conversion Ruby script and multi-pipeline configuration are loaded; real-time data receiving and Schema dynamic mapping are carried out; according to the method, the problems of long link, poor real-time performance, large resource consumption and the like of traditional log processing are fundamentally solved, the architecture is simplified, the delay is reduced, the resource utilization efficiency is improved, and the real-time data processing capability is enhanced.

An adaptive answer-generating agent implemented on a computer system, communicatively connected to a user device, and configured to: receive a user query from the user device; map the user query to one of a plurality of reconfigurable answer-generation schemas stored in first data storage, each of the answer-generation schema specify a sequence of steps to generate an answer output to the query, said agent including an answer generation engine configured to: receive the answer-generation schema mapped to the user query; implement the sequence of steps to generate an answer output, and communicate the answer output to the user device, wherein the agent further includes a schema modification function configured to: receive schema modification data from a further computing device relating to one or more of the answer-generation schemas, and modify the sequence of steps of the one or more of the answer-generation schemas in accordance with the schema modification data.

The invention discloses an intelligent memory scheduling method and device, electronic equipment and a storage medium, and relates to the technical field of memory scheduling and task management. The method comprises the following steps: acquiring data information of a current task, constructing an access mode database, and mapping an access mode into a preset task semantic category by adopting a task semantic classifier; according to the state information of the candidate memory channel, calculating an affinity score of the task semantic category and the candidate memory channel; calculating the priority of the current task through the multi-dimensional features according to the task semantic category of the current task and the user configuration information; according to the load conditions of the candidate memory channels, the target memory channel is allocated for the current task, and memory scheduling of the current task is completed. The method achieves precision and differentiation of memory scheduling, can adapt to service characteristics and resource requirements of different tasks, flexibly adjusts a scheduling strategy according to the system state, and improves the scheduling efficiency. And the utilization efficiency of memory resources is effectively improved.

The invention provides a voucher processing method which can be applied to the technical field of big data and artificial intelligence. The method comprises the following steps: based on a field mapping rule, carrying out mode mapping on preprocessed historical certificates from different service systems according to a standard field unified mode; performing multi-dimensional association processing on the historical vouchers after mode mapping and the multi-source real-time information associated with the historical vouchers to obtain a unified voucher data model; in response to the service request, preprocessing target service associated information associated with the service request, and generating a target service voucher by using the preprocessed target service associated information and the unified voucher data model; and carrying out anomaly detection on the service request by using the preprocessed feature clustering result of the historical voucher, and carrying out compliance check on the generation process of the target service voucher by using a compliance rule determined by the unified voucher data model. The invention further provides a voucher processing system, voucher processing equipment, a storage medium and a program product.

An adaptive answer-generating agent implemented on a computer system, communicatively connected to a user device, and configured to: receive a user query from the user device; map the user query to one of a plurality of reconfigurable answer-generation schemas stored in first data storage, each of the answer-generation schema specify a sequence of steps to generate an answer output to the query, said agent comprising an answer generation engine configured to: receive the answer-generation schema mapped to the user query; implement the sequence of steps to generate an answer output, and communicate the answer output to the user device, wherein the agent further comprises a schema modification function configured to: receive schema modification data from a further computing device relating to one or more of the answer-generation schemas, and modify the sequence of steps of the one or more of the answer-generation schemas in accordance with the schema modification data.

A system and method of tax regulatory change management is provided, comprising: receiving tax filing instructions and e-file schemas of tax forms; converting the filing instructions into output filing instructions and the e-file schemas into output e- file schemas; executing a mapping operation to generate an instruction-to-schema mapping; executing a tax form descriptions operation that generates form descriptions and per-line descriptions of each of the tax forms from the instruction-to-schema mapping using a first generative model; receiving a tax article identifying a tax regulation change; executing an impacted forms operation that uses the form descriptions and the identified tax regulation change as inputs to a second generative model that identifies an impacted tax form; executing an impacted lines operation that uses a third generative model to identify an impacted line from the impacted form; and generating a notification including the impacted line in the impacted form.

A system and method of tax regulatory change management is provided, comprising: receiving tax filing instructions and e-file schemas of tax forms; converting the filing instructions into output filing instructions and the e-file schemas into output e-file schemas; executing a mapping operation to generate an instruction-to-schema mapping; executing a tax form descriptions operation that generates form descriptions and per-line descriptions of each of the tax forms from the instruction-to-schema mapping using a first generative model; receiving a tax article identifying a tax regulation change; executing an impacted forms operation that uses the form descriptions and the identified tax regulation change as inputs to a second generative model that identifies an impacted tax form; executing an impacted lines operation that uses a third generative model to identify an impacted line from the impacted form; and generating a notification including the impacted line in the impacted form.

A system for monitoring data representative of a user's general wellbeing and for delivering digital content to the user, the system comprising a pre-defined module comprising a plurality of reference patterns mapped to digital content for delivery to the user, the system further comprising at least a processing means, wherein the processing means is configured to: identify user activity and select a user based on the identified user activity; for the selected user, interrogate user data representative of the user's general wellbeing and identify a pattern in said user data; and compare the identified pattern to the reference patterns in the pre-defined module to identify digital content mapped with the identified pattern.

The invention discloses a Flume-based time sequence database dynamic adaptation method and device and a medium, belongs to the technical field of databases, and aims to solve the technical problems of how to realize dynamic adaptation of a time sequence database and how to improve the access efficiency of the time sequence database. Comprising the following steps: dynamically loading a driving module of a target time sequence database through a dynamic pluggable protocol plug-in pool; the method comprises the following steps: sampling an input data stream, automatically deducing a timestamp field, an index field and a tag field based on a predefined rule set, and generating a Schema mapping relation of a target time sequence database; dynamically adjusting data batch processing parameters through a reinforcement learning model according to a real-time load index of the time sequence database; and when the time sequence data fails to be written in, a hierarchical retry mechanism is triggered, and the hierarchical retry mechanism comprises local caching, exponential backoff and standby cluster switching.

Systems, computer program products, and methods are described herein for generating and mapping unicode for cross-distributed network data transmissions. The present disclosure is configured to identify a cross-distributed network data transmission comprising source ledger code; generate a core schema for a destination ledger, wherein the destination ledger is based on data of the cross-distributed network data transmission; generate, by a ledger transformation module, a data dictionary, wherein the ledger transformation module receives ledger code from a large language model (LLM); generate code mapping instructions for the cross-distributed network data transmission based on the core schema for the destination ledger; convert the source ledger code to a unicode; receive, by a receiver schema mapping module, the unicode and the code mapping instructions; and generate, by the receiver schema mapping module, an intermediary ledger comprising the unicode and based on the code mapping instructions.

Embodiments of the present application provide a data migration method and device across heterogeneous databases, a storage medium and a program product, relating to the technical field of databases. The method comprises: in response to a migration task, obtaining source data information from at least one source database through a source connector; mapping the source data information into standardized data according to a preset unified data model; inputting the standardized data into a schema mapping engine, and generating target mapping configuration information corresponding to a target database according to a preset mapping rule by the schema mapping engine; converting the standardized data into data in the format of the target database based on the target mapping configuration information to obtain target-ready data; and writing the target-ready data into the target database through a target connector. The method of the present application increases the compatibility of heterogeneous databases and improves the automation degree and processing efficiency of data migration.

A method, system, and computer-readable medium are disclosed for processing and comparing documents in varying formats, incorporating advanced data extraction, normalization, and comparison techniques. The method includes receiving documents containing structured and unstructured data, processing them with optical character recognition and layout analysis to identify structural elements, and extracting key data fields using natural language processing, including named entity recognition and contextual analysis. Extracted data is normalized through schema mapping and synonym resolution, ensuring consistency in terminology and structure. The system employs fuzzy matching algorithms to identify discrepancies between documents and provides an interactive user interface with graphical visualizations, such as heatmaps and comparison charts, for reviewing and resolving differences. Machine learning techniques refine the system over time by integrating user feedback to improve data extraction, synonym resolution, and comparison accuracy.

A method for implementing policy-based compliance enforcement in a federated graph data environment including receiving a query from a query caller for data stored in a graph data storage system, the query including one or more components that are mapped to data entities of the graph data storage system using a schema. The schema expresses connections between data entities of the graph data storage system and includes data classification labels for the data entities of the graph data storage system. Each of the components of the query is examined to identify components to which a policy applies, the identification being done based on the data classification labels. Upon identifying the components, selecting between multiple policy enforcement modes that include reporting violation of the policy, denying query plans in violation of the policy and generating a transformed query plan that complies with the policy. Depending upon the selection, generating the query plan and generating a report that details violation of the policy, preventing execution of the query plan and generating the report that details violation of the policy or generating a transformed query plan.

A process and system for facilitating natural language interrogation of system engineering models is described. The process and system utilize multiple formatting translations of the original SysML model into a graph schema which can be queried by a user using LLM-backed Retrieval Augmented Generation (RAG).

The invention discloses a multi-source data integration management system based on a knowledge graph and a large model, and the system comprises an infrastructure layer which is used for providing hardware support and an operation environment; the data resource layer is used for integrating the structured data and the unstructured data and constructing a knowledge base; the data access layer is used for designing a connection mechanism and completing automatic acquisition and circulation of multi-source data; the data processing layer is used for executing data cleaning, mode mapping, knowledge extraction, knowledge normalization fusion and vector database generation; the knowledge graph layer is used for constructing a knowledge graph including mode definition, graph reasoning, entity management and graph retrieval; and the application management layer is used for designing a double-database collaborative retrieval mechanism based on the vector database and the knowledge graph and realizing business checking and intelligent response. According to the invention, multi-source heterogeneous data can be integrated, knowledge values can be deeply mined, and business intelligent decisions can be endowed.

Artificial Intelligence-assisted building / execution of federated data layer for enterprise engineering: A system trains at least one machine-learning model to identify information about industrial assets from training data, then map the information to a federated data model. The system retrieves information about data from an application in an industrial asset. The at least one machine-learning model identifies types of the data, relationships between the data, and patterns of the data, from the information and based on data types, data relationships, and data patterns in the federated data model. The at least one machine-learning model maps the types of the data, the relationships between the data, and the patterns of the data to the federated data model. The system identifies knowledge about the types of the data, the relationships between the data, and / or the patterns of the data in the federated data model, in response to a query about data.

The invention discloses a data query method and a related device, and the method comprises the steps: receiving a query natural statement sent by a query user, and carrying out the intention recognition of the query natural statement, and obtaining the type of the queried data and the query condition of the to-be-queried data; processing the type of the to-be-queried data and the query condition of the to-be-queried data by adopting a Schema mapping operation to obtain a query type and a query condition suitable for database operation; a query mode is selected based on the query type, a database adapter is selected, the query condition is sent to the selected database adapter, and a query result obtained by the database adapter through query in a corresponding database according to the query condition suitable for database operation is obtained; and inputting the query result into a data management layer for data integration to obtain a data integration result, and outputting the data integration result. According to the method, unified management and output of the data are realized on the basis of adopting corresponding data query modes for different types of data.

An input and processed content associated with a tree data structure is received. It is determined that a correctness associated with a derived pattern mapping associated with a webpage or application is greater than a confidence threshold. The derived pattern mapping that is based on a large language model response is obtained. The derived pattern mapping is utilized to generate a response for the input.

Artificial Intelligence-assisted building / execution of federated data layer for enterprise engineering: A system trains at least one machine-learning model to identify information about industrial assets from training data, then map the information to a federated data model. The system retrieves information about data from an application in an industrial asset. The at least one machine-learning model identifies types of the data, relationships between the data, and patterns of the data, from the information and based on data types, data relationships, and data patterns in the federated data model. The at least one machine-learning model maps the types of the data, the relationships between the data, and the patterns of the data to the federated data model. The system identifies knowledge about the types of the data, the relationships between the data, and / or the patterns of the data in the federated data model, in response to a query about data.

The invention discloses a multi-cloud data analysis method and system based on a cloud platform, and relates to the technical field of data processing. According to the method, cross-cloud security connection is configured, an acquisition agent is deployed, and heterogeneous storage is scanned to generate a structured metadata list and a mode mapping table; constructing a unified metadata directory based on a semantic similarity algorithm, and labeling compliance tags and generating an interactive topological graph in combination with geographic positioning; after a multi-modal request is received, the blood relationship is analyzed, a standardized task descriptor is output, an optimal node is dynamically selected by adopting a four-dimensional evaluation matrix, sensitive tasks pass back an encryption gradient through federated learning fragmentation, and non-sensitive tasks execute homomorphic encryption aggregation; and finally fusing an intermediate result, injecting Laplacian noise to realize differential privacy protection, generating a traceable audit report and automatically recycling resources. According to the method, the problem of multi-cloud metadata splitting is solved, the task cost is reduced, and the over-budget risk is reduced; and the compliance coverage rate and the recovery and utilization rate are improved.

A method can include: (i) obtaining a first data record structured according to a first schema, (ii) determining, for the first schema, one or more first schema attribute values for each schema attribute in a predefined set of schema attributes, (iii) determining, for a second schema, one or more second schema attribute values for each schema attribute in the predefined set of schema attributes, (iv) providing the first and second schema attribute values to a schema matching engine, wherein the schema matching engine contains schema mapping techniques and rules, wherein each rule recommends a schema mapping technique based on schema attributes from the predefined set of schema attributes, (v) applying the rules to select a schema mapping technique, (vi) transforming the first data record according to the selected schema mapping technique, and (vii) providing the transformed first data record in a data structure according to the second schema.

The application relates to a method for constructing an offline simulation model of a power grid based on an EMS system, which comprises the following steps: acquiring CIM / E files and QS files generated by the EMS system in quasi real time; parsing the data contents of the CIM / E files and the QS files into intermediate data sources to form an intermediate view mode; merging the intermediate data sources by establishing a mode matching system to form a global view; querying and screening out target regional power grid data files by adopting an intermediary mode; performing boundary equivalence on the target regional power grid data files, so that the target regional power grid data files pass topological verification and power balance verification; mapping according to a target software format, importing a power system analysis software interface program, and generating an offline power grid analysis model. The method improves the data integration and screening efficiency of the CIM / E files and the QS files of the EMS system by mapping a hierarchical global view mode, and solves the problem of poor timeliness of offline simulation calculation results of the power grid on the basis of ensuring flexibility.

A hybrid cloud bridge system (100) for synchronizing legacy data between on-premises IBM i systems and AWS cloud instances, the system comprising: an on-premises legacy interface module configured to connect to one or more IBM i (AS / 400) systems via native data access protocols, including Distributed Relational Database Architecture and Distributed Data Management, the module further comprising a journal read component for capturing change data in real time from IBM i journal subsystems; a data transformation engine operatively coupled with the on-premises legacy interface module and configured to convert data between the EBCDIC encoding native to IBM i systems and the UTF-8 encoding required by cloud-native applications, the engine comprising an EBCDIC-to-UTF-8 converter, a schema mapping processor, a data validation unit, and a format serializer;a secure communication gateway that establishes encrypted communication channels between the on-premises network and the AWS cloud environment using mutual Transport Layer Security authentication with a pure outbound connection model; a cloud integration module deployed within the AWS cloud environment that includes service adapters for connecting to AWS services; a synchronization controller configured to coordinate bidirectional data synchronization operations via data change detection mechanisms; and a conflict resolution module that implements vector-clock-based versioning to detect and resolve conflicts during concurrent changes;characterized by the fact that the system acts as an intermediary bridge, performing bidirectional real-time synchronization between IBM i legacy systems and AWS cloud instances through integrated data format transformation, secure tunneled communication, and vector clock-based conflict resolution, without requiring any changes to the legacy application code or database schemas.

A computer-implemented Influence Graph Interoperability Layer (IGIL) enables secure and standardized exchange of influence graph data across heterogeneous networks. The system integrates ontology-driven schema mapping, blockchain-based provenance, machine learning identity resolution, permissioned disclosure, and real-time synchronization to generate unified influence graphs. IGIL enhances efficiency, privacy, and auditability for decentralized ecosystems, achieving up to tenfold faster integration and 95% mapping accuracy while preserving data integrity and compliance.