204 results about "Data entity" patented technology

The invention provides an intelligent data consanguinity tracking and visualization method based on graph calculation, and the method comprises the steps: carrying out the data structure analysis and metadata extraction of original data assets, so as to generate a standardized data asset package; performing graph node attribute definition on the data entities in the standardized data asset package, and performing graph edge attribute definition on the association relationship between the data entities to generate a first data blood relationship model; performing blood relationship path mining on graph nodes and graph edges in the first data blood relationship graph model to obtain a basic blood relationship path set, and performing quantitative calculation and feature labeling on path association strength in the basic blood relationship path set to generate a second data blood relationship graph model; and performing visual rule mapping on graph node attributes and graph edge attributes in the second data blood relationship graph model to construct a standardized visual data set and generate a data blood relationship visual interaction interface according to the standardized visual data set.

The invention provides a water conservancy data informatization management system and method. The method comprises the following steps: constructing an object association map of a water conservancy data entity object and business logic based on basic object data, mapping relation data and business logic data in water conservancy data; performing cryptographic hash operation on nodes and connecting lines in the object association map to obtain a data consanguinity fingerprint with uniqueness and tamper-proof characteristics, and storing the data consanguinity fingerprint and an authority strategy matrix for accessing the water conservancy data into an intelligent contract to obtain an authority control contract of the water conservancy data; capturing a data access request of an access user, and determining a data access permission of the access session according to the permission control contract and the data access request; and performing business scene-oriented controlled visual sharing on the water conservancy data extracted from the object association map based on the data access permission. By adopting the scheme of the invention, a water conservancy data security sharing system considering data dynamic adaptation, multi-attribute permission constraint and full-link credible tracing can be constructed.

The invention provides a knowledge graph-driven medical data agent collaborative governance method, system and device and a medium, and belongs to the technical field of medical data governance, and the method comprises the following steps: constructing a knowledge graph containing a quintuple, and defining mapping relationships among medical data entities, attributes and standards; extracting multi-modal medical data knowledge elements through a structured / unstructured engine, and converting the multi-modal medical data knowledge elements into a quintuple for storage; executing table / field / value domain mapping based on the knowledge graph to generate a data mapping result; binding the quality control rules and the medical specifications to form a quality control quintuple; arranging the task into a directed acyclic execution sequence through an agent group cooperation task; and dynamically updating the knowledge graph and performing version management. Medical data full-link governance, knowledge graph unification heterogeneous data semantics, intelligent agent cooperation automatic processing complex tasks, update guarantee knowledge timeliness and quality control rule binding guarantee data quality are achieved, and medical data governance efficiency and accuracy are improved.

The invention relates to the technical field of logistics information management, and particularly discloses a corrugated board logistics information tracking method and system based on RFID, logistics state data of corrugated boards are obtained through RFID and preprocessed, a knowledge graph including entities such as corrugated cartons, storage nodes and transportation tools and association relationships is constructed, the nodes are converted into low-dimensional vectors, and the low-dimensional vectors are stored in a database; key factors and causal effect values which cause anomalies in entity association are mined by utilizing a causal forest algorithm, an abnormal propagation path is reasoned through a graph neural network, a root cause report is generated, targeted decisions such as sorting adjustment, equipment maintenance and path re-planning are generated accordingly, and a graph and a model are updated in real time to adapt to dynamic changes. According to the method, multi-dimensional data, entity relation modeling, causal effect analysis, propagation path reasoning and dynamic optimization design are integrated, the problems of unclear explanation of abnormal root causes and lack of pertinence in decision making in traditional corrugated board logistics tracking are effectively solved, and the accuracy of logistics information tracking and decision making effectiveness are improved.

The invention relates to the field of task automatic decision making, in particular to a task disassembly analysis decision making system and method based on a knowledge graph, and aims to solve the problems that task decision making depends on a structured database, so that decision making lacks deep association, and task target disassembly is easily influenced by personal experience. A data set establishment module specially processes unstructured data, actively extracts data entities, records association relationships, finally generates a dynamic graph, splits a task target into a plurality of sub-task chains, automatically generates a plurality of execution schemes to form an alternative scheme pool, and finally generates an alternative scheme pool through real-time environment data and resource constraint data. It is ensured that evaluation is carried out under the dynamic condition close to reality, the feasibility and accuracy of decision making are improved, deduction is carried out through the graph neural network, chain reactions and potential conflicts possibly occurring in the scheme execution process can be simulated, quantitative risk coefficients are output, risk evaluation is made to be quantitative from qualitative, and the risk evaluation efficiency is improved. And finally, an optimal execution scheme is obtained.

The invention relates to the technical field of data analysis, and discloses a low-code data analysis platform and method based on multi-source data real-time access, and the platform comprises a data access module, a modeling module, a rendering engine and an early warning module. The method corresponds to the platform. According to the method and the device, the problems of real-time integration and standardization of the multi-source heterogeneous data are solved by obtaining the standardized data entity, and a high-quality data basis is provided for subsequent analysis; a dynamically constructed knowledge graph and a graph embedding technology are deeply fused into a data analysis process, so that semantic association among data entities is intelligently understood, an optimized query statement is automatically generated, intelligent recommendation and rationality verification are provided for establishing a data association relationship for a user, and the technical threshold of data modeling is reduced; a second-level response closed loop from data access to visual presentation is formed based on intelligent chart recommendation of data features and early warning rules and instant calculation and triggering in a real-time data stream.

The invention relates to a power operation data processing method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring power data of each data source in a power system; analyzing data attributes of the power data, and converting the data attributes into a predetermined format to obtain target data; based on the target data and the corresponding data attributes, establishing a knowledge graph; wherein the knowledge graph comprises nodes and association relationships between the nodes; when it is monitored that the electric power data of any data source has a change condition, updating the knowledge graph based on the change condition; and screening out key nodes from the knowledge graph, and carrying out real-time monitoring on the key nodes according to an anomaly detection algorithm to obtain an anomaly detection result. Therefore, the knowledge graph is established based on the target data and the data attributes, the dispersed data sources and data entities in the power system are presented in a node form, and the association between the data sources and the data entities is reflected by using the association relationship, so that workers can intuitively understand the internal relationship among the elements of the power system.

This invention provides a method and system for predicting diabetes by integrating knowledge graphs and deep learning. The method constructs an entity vector library of physical examination data, and obtains vector representations of patient physical examination data based on this library, resulting in physical examination data vectors. It then constructs a diabetes domain knowledge graph; based on this knowledge graph, it extracts entities and relationships from patient symptom descriptions and represents them as vectors, obtaining symptom description vectors, and thus a matrix representing the patient's condition; finally, it integrates a self-attention mechanism and a convolutional neural network to construct a classification prediction model, which yields the prediction results. Compared with existing methods, this invention, by simultaneously considering patient physical examination data and symptom descriptions and based on a dual-driven approach of knowledge and data, achieves higher accuracy and interpretability.

The invention relates to the technical field of electric power storage, and particularly discloses an electric power storage resource global collaborative management method and system, and the method comprises the steps: constructing an electric power professional warehouse data graph with an Internet of Things physical ID as a core node, the Internet of Things physical ID being a unique physical identifier of an electric power storage resource; associating material data of a safety supervision warehouse, a regulation and control warehouse and a logistics warehouse, and integrating key data entities of a safety tool verification system, a scheduling equipment management system and a work order management system; a unified data format and a data mapping rule are defined, and standardized interaction of cross-system heterogeneous data is achieved. According to the method, standardized real-time synchronization of cross-system data is realized by constructing a power professional warehouse data graph and relying on an internet of things entity ID active synchronization engine; by using a multi-dimensional rule engine, based on a professional warehouse type-material attribute-business scene three-dimensional rule base, accurate management and control are provided for warehouse-in, warehouse-in, warehouse-out and exception handling of materials, and the asset utilization efficiency is effectively improved.

The invention provides a banking business data change influence analysis method and related equipment. The method comprises the following steps: acquiring a business data blood relationship map constructed for a banking business system; each node in the business data blood relationship map corresponds to each bank data entity, and each edge in the business data blood relationship map corresponds to a data flow relationship among the bank data entities; based on the change type, determining a target sub-graph corresponding to the change type from preset sub-graphs; taking the change node as a starting point, and screening out candidate nodes matched with the root node attribute of the target sub-graph from the business data blood relationship graph; based on the target sub-graph and each candidate node, performing sub-graph matching in the business data blood relationship graph to obtain a matching result isomorphic with the target sub-graph; based on a preset influence scoring rule, scoring each matching path in the matching result; and on the basis of each matching path and the score corresponding to the matching path, a change influence analysis result is generated, so that the change influence analysis efficiency and accuracy are improved.

The invention relates to the technical field of real estate data management, and particularly discloses a real estate data exchange system based on ownership survey data, which comprises the following steps of: establishing an association relationship among a data entity, a processing interface and an operation main body by constructing an ownership data blood relationship network; receiving a data exchange request and extracting context information; extracting a multi-hop association sub-graph from the blood relationship network based on the context information to form a dynamic risk association view; by analyzing a view topological structure, evaluating path sensitivity and connectivity, and quantitatively calculating a single risk value representing a data association leakage risk; and finally, according to a matching result of the risk value and the threshold interval, selecting and executing a corresponding data exchange response action from the security policy library. According to the method, the problem of permission leakage caused by legal operation sequence combination in the prior art is solved, the conversion from static permission control to dynamic risk perception is realized, and the security of real estate data exchange is improved.

The invention provides a security industry compliance risk data processing tracing method and system, and belongs to the technical field of data processing. Comprising the steps that blood relationship original data are collected from various heterogeneous data processing environments in an enterprise, and the data processing environments comprise two different types of ETL tools or data processing platforms; analyzing the collected blood relationship original data to extract the blood relationship among the data entities; the analysis comprises the step of performing variable identification and correction processing on the script containing the parameterized variable; integrating the blood relationship obtained by analysis, and constructing a blood relationship graph covering data flow in the system and cross-system data flow; and storing and visualizing the integrated blood relationship. According to the method, the problems of difficulty in automatic construction of cross-system blood relationship, blood relationship information splitting and incomplete tracing path in the prior art are solved, full-link traceability of security industry compliance risk data is realized, and the method has the advantages of multi-source fusion, automatic updating, high compatibility and the like.

The embodiment of the invention provides a data security management method, system and device, a storage medium and a program product, and relates to the field of data security, and the method comprises the steps: collecting operation behavior data in an application system through a security parallel section technology; constructing an interaction graph between the user and the data entity based on the operation behavior data; analyzing historical operation behavior characteristics in the interaction graph by using a graph neural network model to obtain an anomaly quantized value of each operation behavior data; for any operation behavior data, determining a comprehensive risk value of the operation behavior according to the anomaly quantized value, the data sensitivity weight and the environment risk coefficient; based on the regulation knowledge graph and the comprehensive risk value, generating a corresponding security detection rule; and based on the security detection rule and the comprehensive risk value, executing a corresponding data management and control operation on the data entity in the operation behavior. According to the method, all links of data compliance management can be unified, computing resources are saved, and the management efficiency is improved.

Described herein are techniques for automatically substituting information into orders generated by a data record system prior to persisting the orders in storage of the data record system. The techniques store substitution groups of data entities that store data associated with respective substances (e.g., medications). When order templates (e.g., medication regiments) are generated by the data record system, the techniques automatically modify the order templates (e.g., by substituting data entities in the orders) based on data entity substitution configurations of the substitution groups. Information from the modified order templates is input into orders before the orders are persisted in storage of the data record system.

The application discloses a kind of public dining room food safety supervision method and system in the technical field of food safety supervision.The supervision method includes: S1, for personnel, dishes, agency, event four kinds of data entities, respectively corresponding person code, dish code, agency code, event code Coding rules are formulated;S2, real-time data acquisition generates corresponding code, and establishes the association relationship of dish code and person code, agency code, event code with dish code as connection node;S3, four kinds of data entities and its associated data are stored, and key association data is stored in block chain;S4, receive query request, according to the code of any one kind carried by request, output all data entity information associated with the code.The supervision method breaks the problem of traditional dining room supervision data island in each link, realizes dish, personnel, agency, event data full-link penetration, and any dimension query can quickly obtain complete evidence chain, and key data is stored in block chain, and data credibility is high.

The invention discloses a query intention understanding and execution path optimization system and method based on a multi-modal deep learning model, and the method comprises the steps: a multi-modal intention analysis module is used for receiving unstructured query input from a user, and uniformly extracting the unstructured query input as a standardized SQL; the cross-model intention recognition module is used for receiving the standardized SQL output by the multi-mode intention analysis module, recognizing a data entity, an operation type and a data model to which the data entity and the operation type relate in a query intention, and outputting an entity structure table and a query plan tree; the access mode analysis module is used for using the query plan tree, identifying a connection relationship between node objects in the tree by contrasting with an entity structure table, performing cost estimation on access of each node in the tree, and constructing a logic plan tree; and the path optimization generation module is used for executing generation, evaluation and screening of candidate execution paths on the basis of the logic plan tree output by the analysis module, and finally determining an optimal execution plan. According to the method, the problems of semantic analysis, cross-model query intention recognition and execution path intelligent selection of complex inputs such as natural languages in a multi-mode database can be solved, and the query accuracy and the execution efficiency are improved.

The application discloses a kind of real-time summary method, device, electronic equipment and storage medium of detailed data, it is related to data processing technical field.The method comprises: obtaining different categories of detailed data generated by real-time business system;Wherein, detailed data includes at least one of the following: business data, entity data, rule data and configuration data;In response to the request instruction of target summary index, determine the candidate detailed data matched with request instruction from detailed data;Candidate detailed data is processed based on target data processing model, and target summary result matched with target summary index is obtained;Candidate detailed data and target summary result are rendered and displayed on target display page.The scheme of the application can quickly and accurately determine the summary result of detailed data, and display in the same page, to avoid the inconsistency between detailed data and summary result displayed in the same page provides basis.

The invention discloses a data resource classification and level-to-level management method, system and device oriented to the energy field and a medium, and belongs to the technical field of data management in the energy field. The method comprises the following steps: acquiring a data management range comprising unstructured data and structured data; constructing an initial data directory comprising a plurality of levels according to the data management range; after the unstructured data are converted into structured data, all the structured data are stored in a pre-constructed database, and the structured data comprise data entities and keyword vectors; based on the keyword vector, classifying data entities in all the structured data by adopting a large model technology and a similarity algorithm, and storing a classification result into a corresponding classification hierarchy in the initial data directory to obtain a complete data directory; and based on the complete data directory, grading the data entities which do not reach the preset security classification to obtain a grading result. Unification of data classification and grading standards is realized, and the management efficiency is improved.

Example techniques for providing media assistance data in a telecommunications network (TCN) are described. The media assistance data is received by at least one of a user plane function (UPF) entity of the TCN and a user equipment (UE) connected to the TCN. The media assistance data includes application layer information. Based on the media assistance data, the UPF entity or the UE detects a set of PDUs and determines PDU set information corresponding to the session.

The application relates to the technical field of government affair shared data encryption, and discloses a self-adaptive government affair shared data shape-preserving encryption method and system.The method comprises the following steps: an improved entity recognition model is used to recognize data entities containing potential sensitive contents in original government affair data after structured analysis, and a sensitive label is generated;sensitivity evaluation is performed on the data entities, and an improved clustering algorithm is used to perform sensitive grading processing on the data entities;an adaptive encryption algorithm is used to perform encryption processing and data replacement on the sensitive graded data entities, and government affair shared data is obtained.The application proposes a government affair data protection method fusing entity recognition, sensitivity evaluation and adaptive encryption strategy, a multi-dimensional sensitivity matrix is constructed, potential sensitive fields are finely graded, a matched encryption mode is matched, shape-preserving encryption protection of high-sensitivity entities is realized, desensitization replacement of low-sensitivity entities is realized, and the privacy security and structural usability of government affair data sharing are improved.

The invention relates to the technical field of electrical digital data processing, and discloses a Web application automatic generation and data processing method based on spreadsheet mapping, which comprises the following steps: mapping spreadsheet cells into enumeration values to construct a type fingerprint matrix; calculating a type purity index of a column vector, identifying a vertical blocking band, and splitting the matrix into a plurality of orthogonal sub-matrixes which are not communicated with each other; calculating a type distribution difference value of adjacent row vectors in the sub-matrix to determine a horizontal logic partition line so as to define a logic data block; a Web application object model is assembled based on an arrangement mode of logic data blocks, signal crosstalk between transverse side-by-side data entities is cut off by introducing a vertical topology decoupling mechanism based on column entropy, and the technical problem that downlink feature scanning is easily interfered by orthogonal noise in a multi-table mixed arrangement scene is solved. And the deterministic structure reconstruction of the complex two-dimensional heterogeneous data under the condition of no preset template is realized.

The application discloses a vehicle-mounted Ethernet centralized data management system and method, relates to the technical field of vehicle-mounted Ethernet communication based on a time-sensitive network, and comprises an ECU identification module, a current parameter analysis module, a historical parameter analysis module and a parameter screening module.The ECU identification module is used for extracting ECU units.The current parameter analysis module is used for obtaining the mention rate and the importance of each basic parameter according to the ECU units, and obtaining a first parameter probability.The historical parameter analysis module is used for extracting the query rate and the modification rate of historical parameters, and obtaining a second parameter probability.The parameter screening module is used for obtaining target basic parameters according to the first parameter probability and the second parameter probability.The shortcut entry module is used for obtaining network entries according to parameter entries, and setting shortcut entries according to the network entries.The entity structure generation module is used for generating a distributed data entity structure.The application has the effect of improving the efficiency and accuracy of parameter query and modification of the vehicle-mounted Ethernet in a test development process.

The invention discloses a method for establishing an entity object relationship of urban governance elements. The method comprises the following steps of: firstly, dividing urban governance multi-source data into spatial data and non-spatial data; giving spatial codes to the spatial data according to a spatial grid where a central point of the spatial data is located; especially for the planar elements, a tolerance calculation mechanism is introduced, when spatial overlay analysis is carried out, only when the geometric overlapping relation between the planar elements and other spatial elements meets the preset tolerance calculation condition, it is judged that the planar elements have the inclusion relation and correlation is established, and therefore boundary overflow errors caused by surveying and mapping precision are corrected. And for non-spatial data, accurately mounting the non-spatial data to the established spatial entity through address standardization matching of place name address objects or keyword analysis. And finally, on the basis of a unique space code formed by combining the professional identification code, the space identification code and the time identification code, constructing an urban governance element entity object. According to the method, the problems of inaccurate spatial logic judgment and difficult association of non-spatial data in traditional data fusion are effectively solved, and accurate fusion and efficient indexing of urban governance data are realized.

Various methods and processes, apparatuses or systems, and media for performing a link prediction of a missing node in a knowledge graph are disclosed. The present disclosure provides acquiring the knowledge graph and extracting a set of information from the knowledge graph, the set of information indicates data entities and edges. Each of the edges indicates a relationship between a pair of data entities. The method further includes identifying triplets included in the knowledge graph, in which each of the triplets includes a pair of nodes connected by an edge, and generating an ontological graph model based on the triplets identified and the acquired knowledge graph. The method further performs, via the LLM, a link prediction for the missing node of the knowledge graph based on the generated ontological graph model.

The present disclosure relates to an intelligent customer service system and method based on emotion recognition, equipment and medium, the system comprises: a voice data extraction module for extracting voice data of a user based on a conversation between the system and the user and storing; a word segmentation processing module for performing word segmentation processing on the voice data to obtain word vector data; an entity recognition module for extracting entity keywords in the word vector data and performing first sorting on the word frequency of the entity keywords; an emotion recognition module for extracting emotion keywords in the word vector data and performing second sorting according to the word frequency of the emotion keywords; a decision module for selecting a corresponding response strategy based on a decision algorithm according to the first sorting and the second sorting; a voice module for generating a reply voice statement based on the response strategy. The system and method of the present disclosure recognize user emotions, assist in decision-making, and ultimately improve user service quality.

A system for generating extraction prompts and / or keywords for retrieval augmented data extraction. The system is configured to obtain a plurality of training chunks, where a plurality of first chunks of the plurality of training chunks have the data entity for which the keywords and extraction prompt is being generated. The system generates a first input for one or more language models comprising the data entity for extraction, the plurality of first chunks, and a first request to determine one or more keywords from related to the data entity from the plurality of first chunks. The system also generates a second input for the one or more language models comprising the data entity for extraction, the plurality of first chunks, and a second request to generate instructions to extract the data entity from the plurality of first chunks. The system refines the keywords and the instructions for the extraction prompt.

The application relates to the technical field of electric digital data processing, and discloses a Web application automatic generation and data processing method based on electronic table mapping, which comprises the following steps: mapping electronic table cells into enumeration values to construct a type fingerprint matrix; calculating a type purity index of a column vector and identifying a vertical blocking band, and splitting the matrix into a plurality of mutually unconnected orthogonal sub-matrices; calculating a type distribution difference value of adjacent row vectors in the sub-matrices to determine a horizontal logical segmentation line, so as to define a logical data block; and assembling a Web application object model based on an arrangement mode of the logical data block. The application introduces a vertical topology decoupling mechanism based on column entropy, cuts off signal crosstalk between horizontally arranged data entities, solves the technical problem that a horizontal feature scanning in a multi-table mixed arrangement scene is easily interfered by orthogonal noise, and realizes deterministic structure reconstruction of complex two-dimensional heterogeneous data under the condition of no preset template.

A system and method of property collection management and architecture that can organize patient data while maintaining context is presented. The present disclosure provides for a database system implementing a ‘Property Collection’ as a collection of ‘property name’ and ‘property value’ pairs, which are used to describe a ‘data entity.’ Further, the present disclosure can provide for historical access to data to track data changes. The present disclosure solves the technological problem of accessing data having differing data for the same person. The immutable electronic health record data storage system solves the aforementioned technological problem by providing a blockchain, transaction blockchain API, serialization module, and a deserialization module, among others that can format, process, and store data in a Global Patient Record (GPR).

This invention provides a method, system, medium, and device for RTE optimization of multi-sensor data synchronization, belonging to the field of autonomous driving technology. The method receives multi-sensor data, adds a unified system timestamp, and encapsulates the system timestamp, sensor ID, and the data entity itself to generate a data packet. The data packet is stored in a shared sorting buffer according to the system timestamp. The sorting buffer is checked to determine if a preset release trigger condition is met. When the release trigger condition is met, all data packets that meet the time alignment requirements are retrieved from the sorting buffer and assembled into a synchronization data frame. The synchronization data frame is released through the runtime environment interface. The synchronization data frame is received and directly fused. This method significantly reduces the complexity and development / maintenance costs of application-layer software; achieves deterministic and minimized end-to-end processing latency; improves system resource utilization; and has good versatility and reusability.

The invention discloses a psychological health assessment field knowledge graph construction method and a storage medium. The method comprises the following steps: S1, data preprocessing and structuring: processing an original document of a mental health assessment scale, and converting the original document into scale descriptive text and structured data; s2, entity extraction and seed entity set construction: extracting measurement factors and dimension entities in a single scale range, and constructing a standardized seed entity set; s3, relation triad extraction and deduplication: extracting structural and semantic triads under the constraint of a single scale, and performing semantic discrimination and deduplication by using LLM; and S4, multi-level map fusion and dynamic mapping are carried out, a global three-level semantic skeleton is constructed, entities are normalized and mapped to a standard concept, and problem access and map completion are realized. According to the method, the problems of cross-scale semantic confusion, inconsistent entity granularity and lack of hierarchical logic in the prior art are solved, and the specialty, accuracy and traceability of the knowledge graph are improved.