291 results about "Data dictionary" patented technology

The invention relates to an SQL (Structured Query Language) optimization interaction method and device based on a deep learning framework large model. The method comprises the steps that a statement construction model used for generating and optimizing SQL statements is deployed in a target system; in response to a natural language demand input by a user in the target system, identifying key elements in the natural language demand, and verifying whether the key elements exist in an enterprise data platform connected with the target system in combination with the enterprise data dictionary; inputting the target key elements passing the verification into a statement construction model, and generating a target SQL statement and a corresponding performance optimization suggestion; converting the target SQL statement into a service execution step according to the execution logic, and generating service description information; displaying the target SQL statement and the corresponding generation progress to a user in real time in an interactive interface; and displaying performance optimization suggestions and / or business description information matched with the target SQL to a user in an interactive interface to assist the user in realizing SQL operation related to enterprise business.

The invention discloses an intelligent analysis method and device for an unstructured PDF document, equipment and a medium, and relates to the field of document analysis, the method comprises the steps of obtaining a to-be-analyzed PDF document, analyzing page elements in the PDF document, and generating a document metadata dictionary; if the PDF document does not contain the extractable text, converting the PDF document into an image and performing optical character recognition to generate first structured data; if the PDF document contains the extractable text, judging whether the PDF document contains a table or not; if the PDF document does not contain the table, a PDFMiner is adopted to extract the text, and second structured data is generated; if the PDF document contains the table, performing multi-modal feature extraction and feature fusion on the PDF document according to the document metadata dictionary to obtain multi-modal fusion features, and generating third structured data according to the multi-modal fusion features; according to the method and the device, the analysis precision and efficiency of the PDF document are improved.

The invention discloses a multi-modal heterogeneous medical equipment data fusion and decision support method and device, and aims to solve the problems that the fusion precision is low due to space-time semantic difference of medical equipment multi-modal heterogeneous data (equipment operation parameters, clinical records, fault signals and the like), equipment management decisions depend on experience, and standards are not uniform. According to the method, breakthrough is achieved through three-level data alignment of'time-space-semantics', hierarchical fusion of'data level-feature level-decision level ', three-level decision driven by a knowledge graph and dynamic feedback optimization: time alignment uses a dynamic time warping algorithm, space alignment depends on a unified data dictionary, and semantic alignment introduces an attention mechanism; the feature level fusion quantifies the feature support degree based on the D-S evidence theory; the decision-making layer constructs a'rule-case-prediction 'three-level system, and combines cosine similarity retrieval and information entropy quantification uncertainty. The method and device can support medical equipment maintenance, clinical diagnosis and treatment and other scenes, and the medical service standardization level and the equipment management efficiency are improved.

The invention relates to a low-code visualization optimization method and system for power credential development, and the method comprises the following steps: S1, obtaining data in a credential environment, recognizing the interface difference and performance bottleneck points between components through a compatibility test matrix, and building a standardized adaptive interface specification; s2, obtaining a standardized business object model based on the standardized adaptive interface specification; based on the business object model, defining attributes, relationships and constraint rules of each business entity, and forming a data dictionary and an interface specification special for the electric power field; s3, on the basis of the data dictionary and the interface specification special for the power field, constructing a DSL (field specific language) of power visualization; s4, a dragging type interactive design is adopted, and the visual operation is converted into a DSL configuration file; and S5, automatically converting the DSL configuration into a React or Vue component code through a code generation engine, and carrying out compatibility optimization on the kernel of the creative browser. According to the invention, the power credential development efficiency is effectively improved.

A system (100) for adaptive data blending across heterogeneous BI platforms for real-time decision making, comprising: (a) a data source abstraction module configured to establish standardised and secure connections with several different Business Intelligence (BI) platforms and convert their native data structures into a unified intermediate schema; (b) a real-time data ingestion and synchronisation module operable to continuously monitor and retrieve data updates from the BI platforms using event-driven mechanisms and configurable synchronisation policies; c) an adaptive data mapping and transformation module designed to intelligently harmonize, adapt, and semantically translate disparate data formats using rule-based logic and AI-assisted schema mapping; (d) a semantic context and metadata management module configured to maintain a unified data dictionary, track data sequence and maintain semantic consistency across platforms; (e) a cross-platform query orchestration engine designed to decompose common user queries, translate them into platform-specific query languages, execute them across the relevant BI platforms, and aggregate the results into a coherent output; (f) a decision intelligence and recommendation module that analyses the mixed data to generate real-time insights, alerts and contextual recommendations for decision support; and (g) a security, governance and compliance module configured to enforce access controls, maintain audit trails and ensure compliance with data protection regulations; h) the system provides seamless, real-time and secure data blending to enable consistent analytics and decision-making across heterogeneous BI environments.

The invention provides an ecological environment field-oriented data quality detection method and system based on a large model and a storage medium, and the method comprises the steps: 1, connecting a database, and constructing a plurality of knowledge bases according to the planning of a data governance library and a data dictionary; 2, formulating a general rule, an ecological environment field special rule and a user-defined rule; 3, checking whether the rule is reasonable and effective or not through a prompt template special for a large model in combination with the data consanguinity and the data rule; 4, creating a corresponding scheduling task list according to the current effective data quality rule and the updating frequency; 5, checking the quality problem of the collected data through a prompt template special for a large model, and outputting an analysis report; and step 6, generating improvement suggestions for the problem points found in the step 5 through a large model special prompt template in combination with the situation and reason of the problem. The method has the beneficial effect that the scientificity and effectiveness of rule checking are improved.

The invention discloses an ontology-based data space dynamic access control method and device, and a medium. The method comprises the following steps: constructing a data dictionary connector and a basic connector; establishing a semantic mapping relationship between the global ontology and the local ontology to obtain first access mapping; establishing data field mapping between the data source and the local ontology to obtain second access mapping; performing policy relationship construction on the second access mapping to establish a policy relationship between the data source and the local ontology; obtaining a data request, and determining an accessible field corresponding to the identity of the requester through data access control based on the data request and the first access mapping; carrying out strategy relation analysis on the accessible field to obtain an access query statement; and according to the access query statement, obtaining fine-grained access data through virtual mapping knowledge domain mapping. According to the method, the technical problem that a centralized access control strategy is difficult to respond to the authority change demand in multi-organization cooperation in time is solved.

The invention provides a method and device for extracting report data based on a large model technology, and relates to the field of batch data processing, and the method comprises the steps: carrying out the intelligent table splitting processing of obtained report image data through a pre-constructed intelligent report prompt word project, and obtaining an effective target report; carrying out metadata dynamic extraction processing on the effective target report by utilizing a pre-constructed data extraction cue word project to obtain a report label; performing multi-dimensional data integration processing on the effective target report by utilizing a pre-constructed data integration prompt word project and the report label to obtain a report data dictionary; and performing subject semantic mapping on the effective target report according to the report data dictionary to obtain a required data report. According to the method, a complete automatic processing flow can be constructed, and intelligent report splitting, metadata dynamic extraction, multi-dimensional data integration, subject semantic mapping and the like are realized by combining an optical symbol recognition technology with a large model technology.

The invention discloses a comprehensive traffic infrastructure spatial database construction method based on multi-source data. The method comprises the following steps: S1, collecting road, water transportation and aviation traffic infrastructure data; s2, establishing a data dictionary and a metadata standard according to the specification, and formulating a sub-library strategy and an interface specification; s3, carrying out standardization processing on the attribute data, the satellite image data and the space vector data; s4, formulating a spatial data fragmentation strategy based on a geographic area, constructing a full-text index and spatial index system, and optimizing storage and query; s5, carrying out collaborative management on the K-V storage and the MySQL (Structured Query Language), the PostGIS (Geographic Information System), the MongoDB, the ElasticSearch and the K-V storage; s6, designing an expansion mechanism in the storage layer, the retrieval layer and the calculation layer; and S7, establishing a unified retrieval platform based on the database, fusing grid and vector data, and supporting spatial visualization and semantic retrieval. The method improves the data fusion, retrieval and expansion capabilities of the traffic infrastructure, and is suitable for the construction of a comprehensive traffic information platform.

In one aspect, a computerized method for document extraction workflow for unstructured documents includes the steps of implementing a text mining operation on a set of digital documents the incoming documents. This is done by defining a document type of each digital document. Based on the document type, the method defines a set of data dictionaries to extract any data from each digital document. The method uses the defined set of data dictionaries to extract any data from each digital document.

Disclosed in the present invention is an intelligent energy efficiency management system for an LNG dual-fuel powered trailing suction hopper dredger, comprising: an online intelligent LNG energy efficiency monitoring module, configured to collect energy efficiency key factor parameters of a main energy consumption device of the LNG dual-fuel powered trailing suction hopper dredger to form a unified LNG powered trailing suction hopper dredger energy efficiency data dictionary; an intelligent energy efficiency analysis and evaluation module, configured to construct, on the basis of the LNG powered trailing suction hopper dredger energy efficiency data dictionary, an operating condition identification model, an energy efficiency indicator calculation model, a carbon emission calculation model, an energy efficiency level model and a periodic energy efficiency analysis model to form an energy efficiency analysis and evaluation system; and a dredging operation energy efficiency auxiliary decision-making module, configured to construct an energy consumption prediction model for ten-thousand cubic meters of soil on the basis of soil type, design dredging depth, construction parameters and historical fuel consumption data, and recommending a dredging construction operation parameter combination by means of an optimization algorithm. Also disclosed is an intelligent energy efficiency management method for an LNG dual-fuel powered trailing suction hopper dredger. The present invention increases the energy efficiency.

A system incorporates a platform for analysis of electronic files relating to an old insurance policy using computer protocols such as visual analytics tools to identify attributes of the insurance policy. A policy migration process automates typically complex custom migrations in a methodical workflow employing a simplified metrics-driven process. Layers of a data migration and policy transformation workflow include source policies layer, normalization layer, and target policies layer. The normalization layer includes an extraction, transformation, and loading (ETL) engine. The ETL engine inputs configuration files that incorporate mapping rules for mapping source policies to normalized values within a data dictionary. Systems of the disclosure incorporate built-in personas that cater migration features to a specific set of migration execution team roles such as policy edit and QA. A cloud-based policy migration model includes a UI for inputs by migration team members, and back end components including the ETL engine.

Embodiments of the present disclosure provide large language models (LLMs) and large multimodal models (LMMs) for managing imaging data. An example method includes extracting a database schema and a data dictionary associated with a medical imaging database that maintains medical images and non-image data associated with a plurality of clinical studies; extracting object attributes associated with the medical images that are descriptive of the medical images and corresponding studies; and training an LLM to generate search queries from natural language requests based on a training dataset that includes: the database schema, the data dictionary, the object attributes, a prompt template including partial instructions for the LLM, and a plurality of example natural language requests and corresponding expected search queries. The trained LLM can then be used to generate a first search query from a first natural language request.

The invention discloses a structured data-oriented multi-source feature modeling and multi-granularity intelligent grading and classifying method, and belongs to the technical field of computers. The method comprises the following steps: inputting standardized data to be graded and classified into a currently trained coarse-grained classification model for classification; determining whether the to-be-graded and classified data is subjected to manual auditing or is not subjected to manual auditing; based on a predefined sensitive data dictionary and the final rough classification result, determining a classification result of the data to be graded and classified, and taking the classification result as a fine classification result; using the updated training sample set to perform enhancement training on the currently trained coarseness classification model, and updating the currently trained coarseness classification model based on an enhancement training result; and performing attribution analysis on the fine classification result. According to the method, a set of complete and efficient structured data multi-granularity intelligent grading classification is formed.

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.

The invention relates to a production process-oriented data semantic model construction method and a data storage method thereof, and relates to the field of data modeling. Under the condition that enterprise production needs multi-system collaborative data calling, data of each system is collected, the collected data comprises metadata and a data ontology, mapping processing is conducted on the collected metadata information through a data dictionary, and semantic description is unified; meanwhile, endowing the data ontology with a unique identifier, and mapping the data into a data semantic model according to a data dictionary; the semantic model is divided into a data description layer, a data state description layer and a data context description layer from top to bottom; uniform data semantic modeling is performed on the operation data of the industrial internet, so that massive heterogeneous operation data can be described and managed in a unified manner, and the problem that data between different systems or between the system and equipment is not intercommunicated is solved.

The invention relates to the technical field of gastrointestinal tumor chemotherapy risk assessment, and particularly discloses a gastrointestinal tumor chemotherapy risk scoring model and a construction method thereof, and the method comprises the steps: obtaining the individualized feature data and basic physiological data of a historical patient, and constructing an individualized difference library with a unique ID, and a core influence library; the method comprises the following steps: standardizing and coding double-library data, synchronizing clinical data containing treatment effect codes, forming a data dictionary, acquiring and coding current gastrointestinal tumor patient data, and matching the data dictionary to judge individual difference abnormity; when the first data set is abnormal, constructing a first data set, screening core independent variables through Logistic regression, and constructing a scoring model by using an LSTM (Long Short Term Memory) model; when no abnormity exists, redundant codes are removed to obtain a second data set, and modeling is conducted through the same method. Through double-library linkage and scene-divided modeling, the three-level toxicity risk prediction precision is improved, data support is provided for clinical chemotherapy dose adjustment and toxicity prevention, and the risk of excessive treatment or insufficient treatment is reduced.

The invention provides a database log analysis and recovery method and device, equipment, a medium and a program product, and relates to the field of data processing. Periodically generating a snapshot file of cache record data involved in a database log analysis process, and recording a snapshot identifier corresponding to the snapshot file; updating version information of a data dictionary, and binding the snapshot identifier with the version information of the data dictionary; when database log analysis is interrupted, matching corresponding target version information from the data dictionary according to a target snapshot identifier; recovering the state of the cache record data based on the target version information, and determining the initial position of database log analysis; according to the method, the snapshot file of the cache record data is periodically generated, and the snapshot identifier and the data dictionary version information are bound, so that the cache data state and the analysis starting position are quickly recovered based on the latest snapshot after the database log analysis is interrupted, and the fault tolerance and the recovery efficiency of log analysis are improved.

The application discloses a kind of based on the dynamic calling method and system of AI big model and heterogeneous system of MCP protocol, belong to supply chain intelligent management field, the method includes: according to entity in cold chain warehouse, the data dictionary of cold chain warehouse is constructed to expand standard MCP protocol, identify and extract the system corresponding to entity, and the communication protocol and API of system;Resource pool is constructed in cloud;Dynamic calling layer is constructed in cloud, and dynamic calling layer is called the data of data pool in resource pool by dynamic calling mathematical model, and decision suggestion is generated in combination with AI model in model pool and preset rule set, decision result is encapsulated as MCP instruction message;MCP instruction message is issued to edge gateway, and edge gateway converts MCP instruction message into local instruction executable by system, and is issued to equipment in cold chain warehouse.The application adopts multi-model parallel calling mechanism, realizes the efficient use of system resource and the quick response of task.

The invention discloses a geological data security sharing method and system based on a multi-tenant architecture, and relates to the technical field of geological data management.The sharing system comprises a physical layering architecture, a logic isolation mechanism, a hierarchical management system and a data sharing mechanism, according to the geological data security sharing method and system based on the multi-tenant architecture, through the system and method, by constructing a standardized data interface, an authority grading mechanism and a cross-library collaboration platform, the sharing efficiency and the application value of geological data are remarkably improved, and under a sub-library architecture, the sharing efficiency and the application value of the geological data are greatly improved. The geological data of different units are stored through physical isolation, meanwhile, cross-database data sharing is achieved through unified data dictionary and metadata management, independent data access spaces are provided for different units in a multi-tenant mode, and tenants are allowed to share specific data sets within an authorization range.

The invention relates to an enterprise data analysis method and device, and relates to the technical field of data governance, and the method comprises the steps: carrying out the Text2SQL task fine tuning of a large language model through a low-rank adaptation technology, constructing a structured knowledge base containing an enterprise data dictionary, a field calling relation and a national standard, converting the unstructured industry specification into a structured data standard knowledge base, and realizing knowledge vectorization storage by using an M3E-base vector model; sampling representative samples based on to-be-sorted data fields and retrieving related rules, integrating the representative samples into thinking chain cues, inputting the thinking chain cues into a fine tuning model to generate a labeling classification result, and outputting a data sorting result after multi-model evaluation and verification; generating a regular expression through a retrieval data standard to screen non-standard data, sampling to generate an SQL conversion code, iteratively cleaning until the standard is reached, and outputting standardized data; and finally, executing index optimization and anomaly detection based on the fine tuning model, and receiving natural language query to generate an SQL and a visual report.

The invention provides a user-defined type data access method and system of a database system, and belongs to the technical field of databases. The method comprises the following steps: acquiring a creation service request of a user-defined type structure, establishing a creation request object according to the creation service request, and storing the user-defined type structure of the creation request object to a data dictionary table; then obtaining a read service request, querying and matching a corresponding custom object in the data dictionary table, and generating a read request object capable of executing data storage according to the custom object; executing reading of the request object, and creating a temporary data storage table in a database to store user input data; and assembling all the user input data in the temporary table according to a preset format and returning to the client for display. According to the method, the user can create and read the user-defined type meeting the requirement according to the requirement, and the problem that the standard type of an existing standard database is fixed and inflexible is solved.

The invention discloses a database synchronization method and device, equipment and a storage medium, and the method comprises the steps: reading a pre-writing log received from a source database, and storing all obtained pre-writing log entries into a corresponding transaction array according to a transaction sequence; each transaction array is allocated to a corresponding analysis queue; and when the pre-write log is read, analyzing each analysis queue by adopting the data dictionary to obtain a source end definition data record, and writing the source end definition data record into a target database according to a transaction sequence. According to the method, the pre-written log entries in the same transaction are orderly placed in the same transaction array for processing, consistency in the transactions is guaranteed, the transaction array is allocated to the corresponding analysis queue, the transactions are concurrently processed in different threads, the processing efficiency is improved, the pre-written log entries in the same transaction are orderly processed during analysis, and the analysis efficiency is improved. And the analyzed source end definition data record is synchronized to the target database, so that the database synchronization is improved, and meanwhile, the sequence of transactions is kept.

The invention discloses a discrete manufacturing multi-view BOM dynamic derivation method and system based on a tree-shaped network structure, and belongs to the technical field of intelligent manufacturing and product data management. The method comprises the following steps: constructing a tree body as a single product data source, and storing a hierarchical relationship, attribute definition and engineering semantics of a product in a tree structure; based on the tree body, dynamically matching derivation rules through a mesh mapping relation library; executing rule matching, semantic verification, structure reconstruction and dictionary verification by utilizing a dynamic view derivation engine to generate a target BOM view; semantic constraint and verification are carried out on the derivation process through a BOM data dictionary module; and realizing access control and audit based on role, scene and data sensitivity through the security and authority control module. According to the method, a new generation of xBOM dynamic derivation architecture which takes a tree form as an ontology, takes a net form as mapping, is configurable in rule and is strong in data specification is constructed; the fundamental problem of discrete manufacturing multi-view BOM management is solved, and engineering rationality and service flexibility are both achieved.

The present application relates to the field of automated translation technology and discloses an intelligent translation method and system based on translation forms. The method comprises: upon receiving a first market information form for a target product sent by a Chinese website, determining whether a first translation form corresponding to the target region and the target product exists in an overseas backend system, wherein the first translation form is used to translate the first market information form; upon determining the first translation form, translating the first market information form according to a data dictionary of the first translation form to obtain first translation information; adjusting the format of the first translation information according to the reading habits of the target region to obtain second translation information, and upon determining that the second translation information passes translation quality verification, pushing the second translation information in real time to the overseas site and / or overseas server corresponding to the target region. The present application can accurately translate industry-specific vocabulary and improve information dissemination efficiency.

The invention provides a model-based software development method and device, electronic equipment and a storage medium, and the method comprises the steps: determining whether a data dictionary cache file which corresponds to a target vehicle-mounted software model and is in a native storage format exists under a first cache address in response to an import instruction for the vehicle-mounted software model; if the target vehicle-mounted software model exists, mapping the data dictionary cache file in the native storage format to operate the target vehicle-mounted software model; and if the target vehicle-mounted software model does not exist, acquiring a data dictionary file which is in a general storage format and corresponds to the target vehicle-mounted software model under the second cache address, decompressing the data dictionary file, and performing data analysis and format conversion on a decompression result to operate the target vehicle-mounted software model. By generating the data dictionary cache file in the native storage format in the hard disk in advance and importing the data dictionary cache file into the working space, the data importing speed can be remarkably increased, the simulation running time of the vehicle-mounted software model is shortened, and the development efficiency of the vehicle-mounted software is improved.

The application discloses a kind of based on knowledge base data standard domain automatic generation method and system, it is related to data standard domain generation technical field, method includes: obtaining data dictionary field, retrieve matching candidate standard item from knowledge base and build standard item evidence package containing semantic matching score and evidence source type;Candidate standard item is mapped to standard domain, domain support is calculated and is eliminated by evidence unit exclusion allocation to eliminate shared evidence, and the initial domain distribution of revised domain support is obtained, according to which the initial mode of single domain or multi-domain mode is judged;Calibration is carried out based on domain constraint image, domain change cost coefficient and uncertainty penalty coefficient are generated adaptively according to determination score and conflict score, score function is constructed, refined candidate domain set is filtered out according to initial mode and distribution is reorganized, post-calibration and backflow determination are carried out, and finally single-domain or multi-domain standard domain result is output;The application improves the accuracy and automation degree of data standard domain generation.

The invention provides a data processing method and device, equipment, a medium and a product, and relates to the field of financial science and technology or other related fields. The method comprises the following steps: intercepting an escape data set returned by a service party after receiving a service request sent by a requester, and obtaining a plurality of fields to be escaped from the data to be escaped; to-be-escaped fields in the escape dataset are divided to obtain a plurality of to-be-escaped sets, and the data dictionary is used for storing mapping relations among different fields; using the data dictionary to synchronously perform field conversion processing on each field to be escaped in the set to be escaped to obtain a target semantic field corresponding to the field to be escaped; and using the target semantic field to perform replacement processing on a field to be escaped in the data to be escaped to obtain data after escaped meaning, and sending the data after escaped meaning to the requester. The product provided by the invention can improve the efficiency of the data escape process.

The present invention provides a method and device for recording database table information, comprising: obtaining database information of multiple databases; generating a shell script corresponding to each database based on the database information of each database; using the shell script to read the database table information of each database; generating an md file corresponding to each database based on the database information and the database table information; sending each md file to a Git repository, and using the Git repository to convert the md file into an initial data dictionary; comparing the initial data dictionary with a previously generated historical data dictionary to obtain a comparison result, and updating the initial data dictionary based on the comparison result to obtain a current data dictionary corresponding to each database. The method provided by the present invention can automatically maintain database table information of a database and record relevant differences, thereby reducing the difficulty of subsequent work.