39 results about "Relational system" patented technology

Systems and methods described herein enable adaptive, threshold-based modification of node maps representing ontologies, knowledge graphs, or code development pipelines using generative artificial intelligence. The disclosed platform can retrieve a node map and generate one or more candidate perturbations that modify nodes or relationships within the node map. The disclosed platform can evaluate the effect of the perturbations by comparing respective outputs against ground-truth data. Perturbations can be automatically determined based on changes in external datasets, compliance policies, or operational requirements. The perturbations can be implemented when a computed perturbation quality value satisfies a threshold quality criterion. As such, the system enables efficient, policy-compliant evolution of relational system architectures in dynamic environments.

The invention discloses a teaching course recommendation method and system based on English learning data, particularly relates to the field of semantic processing, is used for solving the problem of poor pertinence of a traditional English learning course, and comprises the following steps: aiming at systematic difference of native language and English expression on a syntactic structure, constructing a language structure difference map and extracting a structure offset label; the method comprises the following steps: performing dependency syntactic analysis on semantic consistent sentence pairs of multi-language aligned corpora to generate a structural difference feature set; on the basis, a semantic-grammar dimension mapping graph is constructed in a classified mode, and a general structure expression vector is established for graph nodes. A teaching course is divided into knowledge point units in combination with a context label, and a mapping relation between a structure label and the course is established. The system performs structure analysis and semantic matching on sentences input by the learner, identifies structure migration type expression errors, and recommends accurate teaching content according to context and structure labels.

The invention relates to the technical field of data processing and analysis, in particular to a knowledge graph entity accurate identification relation system for a service system, which comprises the following steps of: analyzing database table data, extracting an attribute change track and generating an attribute evolution sequence to provide a time sequence data basis for subsequent analysis and ensure the traceability of attribute evolution; meanwhile, the adaptability of the system to heterogeneous data is enhanced; clustering and dividing attribute clusters based on an attribute change mode, establishing a cross-cluster association index, revealing a potential association rule between attributes, and supporting rapid classification and dynamic adjustment of attribute relationships in a service scene; dynamic analysis of intra-cluster and cross-cluster attribute influence is realized by using a bidirectional attribute propagation model, and coupling strength between attributes is accurately quantified through iterative calculation and feedback calibration; by constructing a dynamic attribute topological graph and monitoring attribute value changes in real time, association reconstruction is triggered to generate an attribute association group set, dynamic changes of a service system are adapted, and association accuracy is improved.

The invention relates to an agricultural economy cross-border cooperation English negotiation auxiliary decision-making system, in particular to the field of data processing and analysis, and the system can capture multi-source policy data in real time, construct a policy chain reaction network through dynamic network modeling, effectively evaluate the trade dependency relationship between participating countries, and improve the accuracy of the trade dependency relationship between the participating countries. The system generates a multi-dimensional policy risk score vector based on historical policy data through a risk prediction engine, constructs a multi-objective optimization decision model in combination with a preset negotiation constraint condition, and can output accurate English negotiation policy scripts including clause revision suggestions and interaction sequential logic through a policy optimization generation module. Therefore, accurate decision support is provided for cross-border cooperation negotiation, the cross-border agricultural economic cooperation negotiation method has remarkable advantages in the aspects of improving the decision efficiency of cross-border agricultural economic cooperation, reducing policy risks and optimizing negotiation strategies, the negotiation effect and the agreement achievement rate can be remarkably improved, and smooth proceeding of international trade is promoted.

The invention relates to the technical field of automobile lightweight design and intelligent databases, and provides an automobile lightweight intelligent decision database system and method based on artificial intelligence. The invention aims to solve the technical problems of low design efficiency, low performance prediction and parameter optimization precision and difficulty in balancing multi-target requirements caused by data heterogeneous dispersion, difficulty in intercommunication and information splitting in the existing automobile lightweight design. According to the scheme, an intelligent decision database system is constructed through five core modules: a multi-source heterogeneous data acquisition module realizes data standardization processing and secure storage; the lightweight knowledge graph construction module establishes an association system and dynamically updates a standard; the intelligent algorithm module integrates a deep residual network, Bayesian optimization and a Transform architecture, and completes performance prediction, parameter optimization and scheme generation; the multi-objective optimization decision module screens an optimal scheme through multi-dimensional evaluation and constraint processing; the visual interaction module provides a visual interaction function and supports multi-mode deployment.

A system and method that generates and stores a multivariate time series of the user's conditions and activities, based on the interpretation of the user's natural language input through trained AI including large language models. This time series serves as a comprehensive record of the user's well-being and provides the foundation for the system's ability to identify the factors that most significantly impact the user's desired outcome. By tracking and analyzing the relationships between the various conditions and activities, the system can determine the key drivers of the outcome of interest to the user and provide insights into how to improve and maintain overall well-being.

This invention discloses a method for constructing a relationship-driven cybersecurity knowledge graph. This method, driven by relational semantics, sequentially executes the following steps: multi-source threat intelligence collection and preprocessing, relational semantic modeling, relationship-priority-driven knowledge extraction, entity alignment based on relational context, and knowledge graph construction. By constructing a relational system with entity type constraints and relational reasoning rules, it achieves complete attack chain modeling and implicit relational derivation; it employs a reverse extraction mechanism of relational identification → entity location to reduce error propagation; it introduces relational context to achieve accurate cross-source entity alignment; and finally, it establishes an indexed knowledge graph based on a graph database, supporting efficient querying and attack attribution.

The invention provides a manufacturing decision system-oriented modular functional architecture and a collaborative mechanism thereof, and the structural organization and reusable collaboration of a manufacturing decision process are realized by constructing a multi-layer capability system, a functional module system and a standardized behavior interface. The architecture comprises a data interface module, a decision-making target module, a disturbance response module and a fusion decision-making module, and defines a data flow, a control flow and a trigger relationship among the modules. The system completes target expression, constraint analysis, disturbance identification and collaborative decision generation through standardized access of multi-source data such as orders, productivity, materials and processes, and forms an interpretable and executable decision link. According to the invention, modularization, interpretability and intelligent cooperation of the manufacturing decision-making system are realized, and multi-scene and multi-industry manufacturing decision-making application is supported.

Systems and methods described herein enable adaptive, threshold-based modification of node maps representing ontologies, knowledge graphs, or code development pipelines using generative artificial intelligence. The disclosed platform can retrieve a node map and generate one or more candidate perturbations that modify nodes or relationships within the node map. The disclosed platform can evaluate the effect of the perturbations by comparing respective outputs against ground-truth data. Perturbations can be automatically determined based on changes in external datasets, compliance policies, or operational requirements. The perturbations can be implemented when a computed perturbation quality value satisfies a threshold quality criterion. As such, the system enables efficient, policy-compliant evolution of relational system architectures in dynamic environments.

Profile Information is aggregated from online websites and services to correlate discovered identities to one another via computational analysis of Intra-Personal Relationships, Inter-Personal Relationships, and Profile Data. The information, relationships and content of identities which have been determined to share Intra-Personal relationships are aggregated into Meta-Profiles; the Meta-Profiles are used in place of component Intra-Related identities to optimize computer functions such as social graph operations, content customization, and audience operations (including: analysis, metrics, profiling and targeting). The system processes identities and relationships belonging to individuals registered with the system and those belonging to unregistered users. The system is provided with data from users, via third-party systems, or through automated discovery. These innovations solve problems of online identity disambiguation specific to internet computing, and improve computer operations by optimizing memory footprint and operation calls to minimize the number of nodes and edges traversed.

In the transfer of assets across multiple organizations, it has been difficult to consistently track the chain of proof (chain of proof) and the history of ownership and management (chain of custody) across mergers and separations, and to conduct reliable appraisals and certifications by comprehensively evaluating the authenticity of assets. [Solution] The system acquires data on assets, events, states, assertions, evidence, subjects, and locations from a recording infrastructure, and generates a Chain of Provenance and a Chain of Custody based on this data. Based on the continuity, consistency, and interrelationship of these two chains, it generates appraisal and certification result information including the authenticity level classification (high, medium, low) of the assets.

A system receives a plurality of knowledge objects (KOs). The system receives repository structure definition information, the repository structure definition information specifying one or more repository structure definitions that define respective structures for the one or more data repositories. The system groups the plurality of KOs based on the name, type, and tag attributes of the KOs, and storage paths of the underlying unit of structured, semi-structured, and unstructured data at the one or more data repositories corresponding to the KOs to generate a number of groups of KOs. The system determines a number of compliance categories (CCs), each CC corresponding to a standard on data privacy or data protection compliance mandates. The system determines matching relationships between the CC to each group of KOs. The system generates a first mapping structure that maps relationships between each group of KOs to the CC based on the matching relationship.

The application discloses a kind of construction engineering quality hidden danger positioning screening method and system, the method is by obtaining the structure, material, environment and so on parameter of construction engineering quality hidden danger and classification, data are fused using multidimensional heterogeneous building hidden danger data screening model;Based on the initial search population established by optimized bat positioning algorithm, set fitness function to evaluate individual, update population according to iteration rule until meet termination condition and output hidden danger positioning result.Introduce data fusion, fitness calculation and multiple models in the process, fully consider parameter weight, correlation and coupling relationship.System includes six units such as parameter acquisition, data fusion processing, and each unit cooperates with each other.The application effectively integrates multi-source data, accurately locates construction engineering quality hidden danger, overcomes the defects of insufficient data utilization and inaccurate positioning of traditional technology, realizes efficient and accurate screening of construction engineering quality hidden danger.

Non-mechanistic, differential-equation-free approaches are provided for predicting a particular structure-activity response of a system using a reduced scale and a reduced number of variables. These approaches provide one-to-one relationships between model parameters and model output to obtain a specificity of results between model parameters and model output to get a unique input-response relationship. The systems, methods, and devices (i) reduce the cost of research and development by offering an accurate modeling of heterogeneous and complex physical systems; (ii) reduce the cost of creating such systems and methods by simplifying the modeling process; (iii) accurately capture and model inherent nonlinearities in cases where sufficient knowledge does not exist to a priori build a model and its parameters; and, (iv) provide one-to-one relationships between model parameters and model outputs, addressing the problem of the ambiguities inherent in the current, state-of-the-art systems and methods.

An asset relationship system and method store assets and related data for the asset so that it can be queried. In one embodiment, the asset and the related data may be stored in a graph database in which each node in the graph database stores a piece of asset data and each edge in the graph database encodes a relationship between the two nodes / piece of asset data to which it is connected.

The invention provides a cooperative adversarial iterative learning controller design method based on a communication protocol, and belongs to the technical field of communication information processing. The method comprises the following steps: S1, constructing a cooperation-confrontation system with n nodes, wherein the dynamic characteristics of each node are described by two time scales; s2, designing a communication network based on an RAP protocol so as to avoid data conflicts caused by simultaneous data transmission between nodes and adjacent nodes; and S3, designing an iterative learning controller with a cooperation-adversarial relationship, calculating an error according to the ideal trajectory to realize tracking, designing parameters of the iterative learning controller, and realizing a convergence condition. According to the method, the dynamic tracking problem of a cooperative-adversarial relation system can be effectively solved, data conflicts in signal transmission are reduced, and the target trajectory is tracked more accurately.

Embodiments rank entity importance in monitored networks by analyzing network traffic to collect metrics representing relationships between entities. Network monitoring engines construct network graphs where nodes represent entities and edges represent relationships based on collected metrics. The system employs graph clustering algorithms to partition entities into logical clusters based on interaction patterns. Within each cluster, entities may be ranked by topological importance using metrics to identify primary entities that represent their clusters. Monitoring resources may be allocated preferentially to primary entities from each cluster. The topology-based ranking approach distributes monitoring resources throughout the network.

Techniques for initiating system actions based on text content are disclosed. A system applies a semantic analysis model at run-time to human-understandable text to identify actionable content within the human-understandable text. The system analyzes metadata associated with the text to identify a mapping between one or more data objects associated and the semantic content in the text. The system identifies one or more contact lists associated, respectively, with the one or more data objects. Using a database schema, the system analyzes the contact lists to determine whether to modify the contact lists.

The application provides a display device and a switching method of a WiFi module. The method identifies a target use scenario according to an operation type corresponding to a user interaction action, and evaluates scores of each WiFi module in the scenario in real time based on performance parameters and weight coefficients recorded in a module state library. When the score of a current module is lower than a threshold value, the system automatically switches to a standby module with a higher score, and supports simultaneous operation of multiple modules. By constructing a module state library and a dynamic evaluation mechanism, the problem of poor flexibility of the WiFi module is solved. In addition, a user can customize the allocation relationship between the module and the scenario, and the system dynamically allocates resources according to priorities to prevent stuttering caused by scenario competition. The scheme considers static hardware parameters and dynamic operation indexes comprehensively, so that the system can flexibly adapt to different scenario requirements, significantly improves the use flexibility and resource utilization rate of the WiFi module, and further solves the problem of poor flexibility of the WiFi module.

A system and method for enhancing electronic health record (EHR) systems through integration of proprietary and standardized medical terminologies. Embodiments proprietary terminology concepts from electronic sources and identifies matching standardized medical terminology concepts. A knowledge graph is generated, incorporating both proprietary and standardized concepts along with their relationships. The system receives patient data, including problem lists, medication lists, and lab results. This data is analyzed against the knowledge graph to generate suggestions for the EHR system. These suggestions are then provided to the EHR system for display, enhancing clinical decision support and improving patient care.

The application belongs to the field of power dispatching system automation, and discloses a power grid dispatching control system reliability evaluation method and system based on a multi-dimensional state dependency graph. The application collects node states, slice group states, service call chains, system resource usage, and primary-backup consistency check results and other operation monitoring data, constructs a multi-dimensional state dependency graph (MDDG), and unifies the deployment relationship between nodes and slice groups, the cross-node data access relationship between nodes, the call relationship between services, the system resource competition relationship, and the primary-backup data consistency relationship into a dependency relationship structure, so as to reflect the dependency strength between various operation entities in the distributed dispatching control system, extend the system reliability evaluation from the traditional single-component or single-node level to the system overall structure level, and improve the expression capability for complex distributed architectures.

Methods, system, and non-transitory processor-readable storage medium for a test selection and prioritization system are provided herein. An example method includes mining, by the system, a test case repository comprising test cases and execution results, to identify relationships between test cases based on the execution of the test cases according to a test case execution plan. The system creates a first test case execution plan comprising a first subset of the test cases based on the identified relationships. A test management system executes the first subset of the test cases according to the first test case execution plan on at least one test system. The system assesses results of the execution of the first subset to identify a second test case execution plan, where the second test case execution plan results in test execution failures occurring earlier than test cases executed according to the test case execution plan.

A system queries for entity data of a user from a first data source. The system displays a display panel in a user interface (UI), the display panel including measurement metrics for an account entity of the user from the entity data of the first data source. The system determines mode chaining information that specifies a chain of entity relationships between a number of entities in the entity data, where the relationships include one-to-one or one-to-many relationships. The system determines forecast information corresponding to the measurement metrics for the entities of the user. The system displays the forecast information as entity-based forecast values in the UI based on the mode chaining information, where the entity-based forecast values include a drill down of forecast values for the entities of the user.

To migrate a volume between nodes without suspending an I / O request from a host in a storage system that includes a plurality of storage nodes.SOLUTION: In a system S that includes a first storage system and a second storage system, there is a nonsynchronous-copy pair relation between a first volume of the first storage system and a second volume of the second storage system. The system S creates, with the second volume being as a volume subjected to migration, a copy volume of the second volume in the other storage node in the second storage system. Next, the system reflects, in the copy volume, difference data between the first volume and a snapshot of the first volume. Subsequently, the system newly creates a nonsynchronous-copy pair relation between the first volume and the copy volume in such a way that data on an I / O request from a host to the first volume is reflected on the copy volume in a nonsynchronous manner.SELECTED DRAWING: Figure 16

The systems, methods, and / or instrumentalities disclosed herein can involve adjusting an automated cooperative operation based on a situation-derived constraint. A system can be configured to receive a first data stream and / or a second data stream from a first surgical element and / or a second surgical element. The second data stream can be indicative of a second output parameter associated with a complementary task. The system can determine a relationship between the first surgical element and the second surgical element based on the first data stream and / or the second data stream. The system can determine a boundary parameter associated with the second output parameter based on the first output parameter and / or the relationship. The system can communicate an indication of the boundary parameter to the second surgical element. The system can cause the second surgical element to perform the complementary task based on the boundary parameter.

A request that specifies a logical address associated with a host-initiated operation directed at a first portion of a memory device is received. A logical to physical (L2P) table is accessed. The L2P table comprises a mapping between logical addresses and physical addresses in a second portion of the memory device. An entry in the L2P table that corresponds to the logical address is identified and is determined to point to an entry in a read cache table. Based on an entry number of the entry in the read cache table, a chunk address of a chunk from among multiple chunks of a read cache is calculated. A physical address that corresponds to the logical address specified by the request is identified by accessing the chunk of read cache. The host-initiated operation is performed at a physical location within the first portion of the memory device corresponding the physical address.

Embodiments of the present disclosure relate to comparing network topology, state, and configuration at different time instances. A network management system for orchestrating a network is provided. During operation, the system generates a graph representing the network. Respective vertices correspond to entities in the network, and respective edges indicate relationships between pairs of vertices. The system can determine, for respective edges, first and second timestamps. The first timestamp indicates a time instance when the relationship indicated by the edge was established. The second timestamp indicates a time instance when the relationship was terminated. A time range between the first and second timestamps indicates a valid time period for the edge. The system then receives, from an interface of the system, an instruction to compare topology, state, and configuration of the network. The system determines, by traversing valid edges of the graph, a topology, state, and configuration of the network at a target time instance indicated by the instruction.

The invention provides a traditional Chinese medicine cross-language aided translation system based on artificial intelligence, and belongs to the technical field of traditional Chinese medicine translation. The traditional Chinese medicine cross-language aided translation system based on artificial intelligence comprises a data acquisition module, a semantic recognition module, a semantic correction module, a translation strategy output module and a translation evaluation module. The system can track semantic distance changes between term translation and historical standards in real time, a translation migration file is established for recognized deviations, the corresponding relation between word meaning drift paths and contexts is recorded, the system can judge whether the deviations belong to common error types or not, rapid error correction is conducted on the basis of a term evolution database, and therefore the accuracy of term translation is improved. The mechanism does not depend on a fixed dictionary rule, but performs combined judgment according to factors such as a semantic change trend, a context structure adaptation degree and the frequency of historical deviation behaviors, so that the intelligence and the adaptability of deviation judgment are greatly improved, and the self-correction capability and the fault tolerance of a translation system are remarkably improved.

The invention discloses a hydrological dynamic monitoring and analysis method based on an entity map, and relates to the technical field of hydrological dynamic monitoring and analysis based on the Internet of Things, and the method comprises the steps: constructing a hydrological entity map of a target watershed, abstracting a hydrological object into an entity, defining a time-space association relation of the entity, and after a system responds to a request, carrying out the analysis of the entity map. A polymorphic monitoring view strictly corresponding to the entity map is displayed, when a user operates a specific view, the system traverses the map from a root node entity and dynamically outputs a monitoring result, and intelligent guide analysis is achieved. The system supports unified conversion of multi-source heterogeneous hydrological data, and the time-space relation clearly covers key associations such as space inclusion, flow direction, monitoring dependence and event triggering. Each hydrological entity model integrates multi-dimensional attributes, supports from basic monitoring to intelligent analysis and early warning decision, and realizes unified fusion of hydrological monitoring data, precise modeling of a time-space relationship, dynamic guidance of an analysis path and effective support of early warning decision.

A system may display a Graphical User Interface including a source region presenting a plurality of source data-serialization elements and a destination region presenting a plurality of destination data-serialization elements. The system may receive a user input associating a first destination data-serialization element, of the plurality of destination data-serialization elements, and a first source data-serialization element of the plurality of source data-serialization elements. Responsive to receiving the user input, the system may generate and store a mapping expression that defines a mapping association between the first source data-serialization element and the first destination data-serialization element. The system may present in a mapping region of the GUI displayed concurrently with the source region and the destination region, a mapping element representing the mapping association between the first source data-serialization element and the first destination data-serialization element.