13 results about "Standard data model" patented technology

The invention discloses a cross-platform advertisement data fusion analysis method and system based on multi-source heterogeneity, and relates to the technical field of data fusion and advertising, and the method comprises the steps that a multi-source heterogeneous data collection module collects multi-platform advertisement data through a standardized interface to generate an original data stream; the data standardization module maps each platform differentiation field to a standard data model; the entity alignment module performs cross-platform entity matching based on material fingerprints and account features; the time sequence alignment module performs data aggregation according to a unified time granularity; the cross-platform attribution analysis module tracks a conversion path and calculates an attribution weight; according to the cross-platform advertisement data fusion analysis and closed-loop optimization system and method, the problems that cross-platform advertisement data formats are not uniform, entity alignment is difficult, time sequences are not synchronous, attribution analysis is inaccurate and the like are solved, and fusion analysis and closed-loop optimization of the cross-platform advertisement data are achieved.

The invention discloses a terminal test system and method based on a DL / T698 protocol. The system is composed of a master station platform, a to-be-tested terminal, a virtual electric meter, a virtual router and a data driver. The master station platform integrates a master station control module, a test case module, a configuration and control module, a communication management module and the like to realize test instruction initiation, parameter configuration, data interaction and result judgment; the virtual electric meter simulates a real electric energy meter to generate standardized data, the virtual route guarantees message transmission between the terminal and the communication connector, and the data driver provides a standard data model for result verification. The test method comprises a plurality of stages of pre-configuration and environment establishment, test case construction and data preparation, test step code conversion and assertion setting, test execution and result feedback and the like. According to the invention, the test efficiency can be greatly improved, the labor cost is reduced, and the test accuracy and reliability are improved.

The present application relates to a kind of metadata-driven two-dimensional standard data automatic storage method, belong to coal mine informatization technical field, including the following steps: S1: construction metadata system and define two-dimensional standard data model specification, generate standardization data model specification document, the metadata system includes data structure metadata, constraint metadata and storage adaptation metadata, the model specification is clear two-dimensional data's row dimension rule and automatic storage trigger condition;S2: by ETL tool, establish target data with the dynamic mapping association of the data model specification, generate and include field mapping relationship, conversion rule and storage routing information's mapping configuration;S3: based on the data model specification and mapping configuration, trigger automatic storage process, including automatically parsing model specification generation storage structure, automatically match storage medium, automatically execute data write and check, realize the automatic storage of two-dimensional data.

The application discloses a data migration method and device, electronic equipment and storage medium. The method comprises the following steps: constructing a hierarchical node graph according to demand elements of a data migration system under multiple demand types; different demand types are located in different levels; obtaining a standard data model matched with at least one data migration system respectively, the standard data model is used for storing the mapping relationship between multiple elements of the data migration system, and two elements in each element mapping relationship belong to different demand types; establishing the mapping relationship between demand elements in adjacent levels in the hierarchical node graph according to the standard data model, forming a migration mapping relationship graph; and migrating data in each data migration system to the data migration system according to the migration mapping relationship graph. Through the technical scheme, the data migration process based on data assets can be automated, the workload of manual data migration is reduced, and the data migration efficiency is improved.

The invention discloses a full life cycle data governance method and system based on data assets. Comprising a data asset inventory and identification module, a data architecture design and organization module, a data standard formulation and management module, a data model design and management module, a data quality management and auditing module, a data security management module, a data asset panoramic display module and a data standard definition and quality auditing tool module. The data asset checking and identifying module is used for comprehensively checking all data assets in an enterprise and identifying the source, the type, the use condition and the storage mode of the data; the data assets are checked and organized, the functions of data asset panorama, data map, data standard, data model, data quality and the like are provided, effective management of the data assets is achieved, in addition, a data standard definition tool is further provided, visual modeling and configuration rules are provided for quality auditing, and the data assets can be effectively managed. And the data quality is further improved.

The invention discloses a standardized data asset directory construction method and device, equipment and a program product, and relates to the technical field of data management. At least one target metadata in a database is subjected to word segmentation and translation correction processing to generate words of the at least one target metadata, and the words are subjected to standardized definition based on at least one standard and / or large language model to generate data standards. In this way, automatic generation of data criteria is achieved by employing a natural language processing technique, at least one criterion, and a large model technique. And performing standardization processing on the target metadata based on the data standard to generate standardized metadata, and classifying the standardized metadata to obtain a standardized data asset directory. Compared with the mode of designing the standard data model and carding the data asset catalog through manual operation or a script semi-automatic mode, the standard metadata and the standard data asset catalog are automatically generated based on data standard processing, and the efficiency of generating the standard data asset catalog is improved.

The application provides a data model structure mapping method, system and terminal, which synchronizes and supplements metadata of a to-be-mapped data model structure, generates a corresponding original operation data storage model through the supplemented metadata of the to-be-mapped data model structure, performs a mapping operation on the to-be-mapped data model structure based on a pre-constructed table field mapping large language model, maps the to-be-mapped data model structure to a preset standard data model structure, generates a corresponding data model mapping relationship and a data model mapping script, thereby replacing an artificial mapping mode, reducing mapping time consumption, reducing mapping cost, improving mapping efficiency and accuracy, and solving the technical problems of large artificial workload, high cost, low efficiency, dependence on artificial experience, poor accuracy, reliability and traceability in the prior art of mapping each data model structure by using an artificial mapping mode.

The invention discloses an AI-based interface model automatic conversion system, which comprises an AI analysis module for identifying interface model information in a document and converting the interface model information into a fixed format text containing a field name, a field meaning and a data type; the AI mapping module is used for mapping partner interface fields into local internal standard data model fields and assembling a mapping relation in a JSON format; the knowledge base management module is used for storing historically completed model mapping configuration and content results of subsequent AI configuration; the content with incorrect configuration is fed back to the AI mapping module through API (Application Program Interface) calling; the AI integration and calling module is used for integrating a large model by using Spring AI and calling the large model through ChatClient to realize interaction; and converting an AI processing result into a format meeting system requirements by customizing an output model format. According to the invention, rapid and accurate conversion of the interface model can be realized.

The invention provides a heterogeneous data fusion method and device based on a bridging technology, equipment and a medium, and belongs to the technical field of data processing.The method comprises the steps that source data are obtained, data extraction is conducted on the source data, and metadata in the source data are obtained; aiming at each source field in the metadata, matching the source field with a standard field in a preset standard data model to obtain the standard field matched with the source field; determining a mapping rule based on a matching relationship between the source field and the standard field, and mapping the source data to a standard data model based on the mapping rule to obtain converted source data; and fusing the multi-source heterogeneous data based on the converted source data. According to the heterogeneous data fusion method and device based on the bridging technology, the equipment and the medium provided by the invention, efficient and reliable data fusion can be realized.

The invention discloses an intelligent fire early warning system and method applied to an electric power system, and relates to the technical field of knowledge maps, and the method comprises the steps: collecting all fire detection points and corresponding sensor equipment in the electric power system, defining an equipment-detection point-event standard data model, and forming a spatio-temporal data lake; constructing a power equipment fault-fire knowledge graph by using the entities and the entity relationship; constructing a space-time correlation clustering mechanism to obtain a comprehensive alarm event, and generating a comprehensive evidence set according to the power equipment fault-fire knowledge graph; calculating an evidence matching result by using a Bayesian network, and outputting a posterior probability to obtain a fault type of the comprehensive alarm event; performing path reasoning according to the fault type in the power equipment fault-fire knowledge graph, outputting all subsequent nodes related to the fault type to form a consequence chain, and automatically generating an interpretable comprehensive alarm report; and calculating a reasoning confidence score, and setting a verification-updating mechanism to update the power equipment fault-fire knowledge graph.

The invention relates to the technical field of data alignment processing, in particular to a knowledge graph data mode alignment method and an entity data extraction method. An equipment body comprises an equipment layer and an edge layer, the equipment layer is responsible for collecting original data, a data preprocessing engine deployed on the equipment layer extracts a data entity from the original data, then the equipment layer sends the data entity to the edge layer, the edge layer sends a query request to an edge node storing a knowledge graph database, and the edge node stores the knowledge graph database. According to the method, a data entity is stored in an edge layer to inquire a target knowledge graph matched with the data entity from a knowledge graph library on the edge node, then the edge layer loads the target knowledge graph, and the edge layer converts the data entity into a standard data model based on the target knowledge graph to achieve data alignment processing. The data alignment processing is to convert the form of a data entity into a unified standard data mode. According to the analysis, the required target knowledge graph is loaded to the equipment body in a query mode instead of loading a huge knowledge graph library to the equipment body, so that the equipment body can complete data mode alignment processing of the original data on the equipment body by utilizing the knowledge graph; the target knowledge graph is much smaller than a complete knowledge graph database, so that the data mode alignment processing efficiency can be improved.

The invention discloses an attendance checking method and system based on a rule engine and a storage medium, and belongs to the technical field of computers. The method comprises the following steps: establishing an attendance standard data model based on a rule engine in a B / S (Browser / Server) architecture, and outputting attendance information to a target management system in response to a trigger event by the standard data model by taking multi-source data as input; wherein on the basis of the rule engine, the formats of the multi-source data are unified to adapt to the standard data model, and the format of the attendance information is changed to adapt to the target management system. The attendance checking method can effectively solve the technical problems of difficulty in function expansion, high data processing cost, easiness in making mistakes and low iterative maintenance efficiency of an attendance checking method in related technologies, can also effectively solve the problems of poor scene adaptability and poor abnormal management and control capability, and meets the new requirements of enterprise attendance checking management.