1452 results about "Data field" patented technology

The present disclosure provides a method and system for orchestrating automated data processing and transformation. A centralized orchestrator receives a request to process a client dataset and initiates a data ingestion process to obtain sample data. A semantic analysis module analyzes the sample data to determine semantic types of data fields. A transformation module generates data transformation instructions based on the determined semantic types. The orchestrator deploys a data processing pipeline to a client-controlled environment and configures privacy preservation parameters to identify and obfuscate potential personally identifiable information. The pipeline applies the transformation instructions and privacy parameters to the dataset. A configuration module determines data storage configurations for the transformed dataset. The transformed dataset is stored according to the configurations in a client-controlled or cloud environment. A machine learning module generates a model based on the transformed dataset, which is stored in a model repository accessible to the client.

The invention relates to the technical field of application of information technology in constructional engineering, and discloses a method for intelligently extracting engineering quantity application in highway engineering. The method comprises the following steps: standardizing an engineering scale in highway engineering design to form a standardized engineering scale; establishing a preliminary budget project reference template; establishing a connection relationship between the preliminary budget project reference template and the standardized engineering scale, wherein the connection relationship at least comprises a semantic correspondence relationship between project sections and engineering scale fields, a logic matching rule between quota subitems and engineering parameters, and a self-adaptive adjustment mechanism for table format differences; when a new engineering quantity table is imported, automatically identifying and analyzing a data field and a structure of the new engineering quantity table based on a connection relationship, mapping data in the new engineering quantity corresponding table to a corresponding project section and a quota sub-target of a preliminary budget project reference template through semantic analysis and a logic matching rule; and generating a budget file meeting the cost compilation requirement.

The invention discloses an intelligent storage system supporting multi-source heterogeneous data fusion management, which relates to the technical field of multi-source heterogeneous data fusion, and comprises a data source adaptation module, an intelligent data source adapter is configured in a DataWorks data integration module, multi-source heterogeneous data is accessed through the intelligent data source adapter, and the data source adaptation module is connected with the DataWorks data integration module; extracting a semantic feature vector and a technical feature set; the neural symbol hybrid inference module inputs the semantic feature vector and the technical feature set into a neural symbol hybrid inference engine, calculates a similarity matrix between multi-source heterogeneous data fields through a BERT-based neural network, and imports the technical feature set into a field knowledge graph constructed by Neo4j for symbol logic verification to generate a unified metadata model; according to the method, a semantic similarity matrix calculated by a BERT-based neural network is combined with symbol logic verification of a Neo4j knowledge graph through a neural symbol hybrid inference engine, so that automatic semantic alignment and logic consistency verification of multi-source heterogeneous data are realized.

A system and method for root cause analysis in incident processing, including root cause change detection, is presented. The method includes processing a plurality of event records, including a plurality of alert records and a plurality of change records, each event record generated based on an event in a computing environment; parsing each alert record based on a predetermined data field; extracting from each predetermined data field a data value; correlating a group of alert records of the plurality of alert records based on at least an extracted data value; generating an incident data record based on the extracted data values of the correlated group of alert records; detecting a change record of the plurality of change records related to the incident data record; determining that the change record is a root cause change of the incident data record; and initiating a mitigation action based on the root cause change.

The invention relates to the technical field of information and data processing, in particular to an enterprise digitalization-oriented data management and application method, which comprises the following steps of: acquiring multi-source heterogeneous data and recording metadata; establishing a cross-department management system to standardize the treatment process; building an asset catalog based on the business section and the data field classification; formulating unified data description of a multi-level data standard system; designing a quality control rule to filter low-quality data; constructing a business index system and embedding the business index system into a business system; identifying a cross-system and cross-type association mode through a metadata association technology and a rule engine; and dynamically adjusting the treatment process by adopting a multi-objective optimization algorithm in combination with service feedback and treatment parameters. According to the method, the defects of existing data governance in comprehensiveness, depth and business adaptability are overcome, standardized governance and potential value mining of multi-source data are achieved, and effective data support is provided for intelligent decision making of enterprises.

The invention provides an enterprise data sharing method and system based on ai driving, and relates to the technical field of ai data processing.The enterprise data sharing method comprises the steps that firstly, field semantic vectors are built based on information such as field names, description, example values and affiliated process positions, and semantic tag normalization is completed through a lightweight model; then, a field generation path diagram is automatically constructed through a behavior log, field static semantics and dynamic process behaviors are fused, and modeling is carried out on field generation dependency; fusing field semantic information and an access request context, including dimensions such as an access role, a module, access time and the like, dynamically generating a sharing control rule through a policy model, and defining a sharing permission, a desensitization mode and a return granularity; mapping the strategy into an actual sharing execution action, and realizing control-level response to a data field; according to the scheme, the problems of semantic inconsistency, process isomerism and strategy rigidity can be effectively solved, and the data sharing precision, safety and intelligent level between enterprises are remarkably improved.

The invention relates to the technical field of data processing, can be applied to the field of science and technology finance / digital medical treatment, and discloses a multi-source heterogeneous data verification and tracing method and device and related equipment. The method comprises the following steps: acquiring multi-source heterogeneous data from a service data source of a target service; preprocessing the multi-source heterogeneous data, extracting a first data field in each data source, and matching the first data fields with the same semantics in different data sources based on a preset semantic mapping rule; performing consistency verification on the matched first data fields to obtain second data fields with inconsistent verification results; performing root cause tracing on the second data field based on a preset difference analysis rule, and determining a difference type corresponding to the second data field according to a root cause tracing result; and generating a multi-source heterogeneous data verification and tracing result according to the business data source, the second data field, the root cause tracing result and the difference type. According to the method, matching, difference identification and root cause positioning of multi-source heterogeneous data are realized.

The invention discloses a multi-protocol device data conversion method, device and equipment based on a red-mine system, and a medium. The method comprises the following steps: acquiring a first protocol data frame sent by a first protocol host; analyzing the protocol data frame to obtain at least one piece of equipment data information contained in the protocol data frame; according to a predefined mapping relation, mapping each piece of equipment data information to a standard data field based on a second protocol object model; and performing data encapsulation on the mapped data according to a second protocol format to generate a second protocol data frame, and sending the second protocol data frame to a second protocol client application in the Hongyu system through a second protocol server. Seamless joint between the industrial field equipment and the intelligent mine system is realized, and the data transmission efficiency and the system compatibility are obviously improved.

The invention provides a multi-class business data importing method and device, electronic equipment and a storage medium, and is suitable for the fields of financial science and technology and medical services. The method comprises the steps of obtaining a business data import request, a corresponding business data file and a target data table; analyzing the business data file to obtain a business file format, and determining a target analysis rule in a preset analysis rule base; performing field analysis on the business data file based on the target analysis rule to obtain multiple pieces of data field information; for each piece of data field information, matching the data field information with each piece of target field information to determine an import mapping relationship between each piece of data field information and the target field information; performing structured splitting on the business data file according to the target analysis rule to obtain structured business data; and importing the structured business data into the target data table according to the importing mapping relation. The method and the device can improve the efficiency of importing multiple types of business data into the database.

The invention belongs to the field of data processing, and particularly discloses a method and system for automatically generating a document according to a template and structured data, and the method comprises the steps: processing an archive template file according to a document object model analysis method, extracting the position, the type and the associated tag of a placeholder, and obtaining a placeholder metadata set; according to the placeholder metadata set, traversing a document hierarchical nesting relationship by adopting a depth-first search algorithm to obtain a hierarchical placeholder mapping table; obtaining the structured data of the document repair record through an external data source, judging whether the structured data field corresponds to the tag in the mapping table according to the hierarchical placeholder mapping table, and if so, generating a matching pair list from the field to the placeholder to obtain a preliminary matching data set; the objective of the invention is to solve the problem of a business scene in which complex nested data and file template placeholders cannot be accurately matched in a document repair record in the prior art.

A system and method for reducing data record processing in incident report generation is provided. The method includes: accessing a plurality of event records, each event record generated based on an event in a computing environment; parsing each event record based on a predetermined data field; extracting from each predetermined data field a data value; correlating a group of event records of the plurality of event records based on at least an extracted data value; generating an incident data record based on the extracted data values of the correlated group of event records; generating a prompt based on the incident data record; and generating an incident report by configuring a large language model (LLM) to execute the generated prompt.

The invention discloses a reservoir management optimization method and system based on digital twinning. The method comprises the steps of multi-source data acquisition and virtualization mapping, digital twinning modeling, reservoir risk early warning and reservoir management decision optimization. The invention relates to the technical field of reservoir intelligent management, in particular to a reservoir management optimization method and system based on digital twinning, and the method comprises the steps: constructing a virtualization data field through multi-Bezi wavelets and fractal interpolation, and carrying out the self-learning of dynamic weight fusion through a time sequence convolution network; constructing a macroscopic twinborn body and a microcosmic twinborn body, and coupling through an asynchronous message bus; constructing multi-source risk vectors of water pressure gradient, over-overflow water level, dam body stress and seepage flow, adopting clustering and spatial diffusion, generating a dynamic risk thermodynamic diagram, and performing early warning; by taking flood control safety, water supply guarantee and ecological environment as multiple targets, a multi-target particle swarm optimization model and flow constraints are established, an optimal scheduling scheme is solved and executed in real time, and high-precision simulation, precise early warning and intelligent scheduling are realized.

The invention relates to the technical field of mine safety and geological environment evaluation, in particular to a mine goaf geological environment dynamic evaluation method based on digital twinning. The method comprises the following steps: constructing a digital twinborn model of a mine goaf, designing a data structure and a virtual-real mapping rule, collecting multi-source heterogeneous data, and performing spatio-temporal data indexing processing to form a spatio-temporal associated data stream; microseismic travel time data are extracted from the space-time associated data stream; performing parallel ray tracing and rapid inversion on the microseismic travel time data to obtain a wave velocity distribution initial value; carrying out wave velocity field self-adaptive grid refinement on the micro-seismic travel time data by utilizing the wave velocity distribution initial value to obtain a multi-resolution wave velocity field; and carrying out wave velocity change rate analysis on the multi-resolution wave velocity field to obtain a wave velocity variability tensor. According to the method, the abstract energy transfer process is concrete into a data field capable of being quantitatively analyzed, so that the geological environment of the goaf is accurately and dynamically evaluated.

The invention belongs to the technical field of artificial intelligence, and relates to a data query method and device, computer equipment and a storage medium. Performing semantic analysis on the query information to obtain a semantic analysis result; performing data source matching and data field extraction on a preset metadatabase based on the semantic analysis result to obtain a data source positioning result and a data field extraction result; constructing statistical logic based on the semantic analysis result and the data field extraction result; obtaining a target retrieval statement template based on the semantic analysis result; performing parameter filling on the target retrieval statement template based on the semantic analysis result, the data source positioning result and statistical logic to obtain a big data retrieval statement; performing query processing on the business data based on the big data retrieval statement to obtain a query result; and sending the query result to the user. The method can be applied to data query scenes in the fields of finance, medical treatment and the like, and the processing efficiency and accuracy of data query are improved.

A system for converting a source data feed schema into a canonical data product including a memory for storing computer-executable instructions and a processor for executing the instructions stored on the memory. Execution of the instructions programs the processor to perform operations that include receiving a source data feed having a source schema, identifying a plurality of data fields of the source schema, assigning a data category from a plurality of predefined data categories to each data field of the plurality of data fields, modifying the source schema based on predefined parameters, wherein the source schema is modified to match a target schema, comparing the modified source schema to the target schema, and in response to a determination that the modified source schema matches the target schema, converting the source data feed to a canonical data product having the target schema based on the assigned data categories.

A system and method for identifying device attributes based on string field conventions. A method includes applying at least one machine learning model to an application data set extracted based on a string indicated in a field of device data corresponding to a device, wherein each of the at least one machine learning model is trained based on a training data set including a plurality of second strings and a plurality of device attribute labels, wherein each device attribute label corresponds to a respective second string of the plurality of second strings, wherein each of the at least one machine learning model is configured to output a predicted device attribute for the device based on the first string; and identifying, based on the output of the at least one machine learning model, a device attribute of the device.

The invention relates to a cross-domain voice classification method and device based on feature decoupling and multi-task learning. The method comprises the following steps: firstly, acquiring a multi-data-domain voice file, and preprocessing the multi-data-domain voice file to obtain a cross-domain voice classification data set; then, constructing a cross-domain voice classification model which comprises a voice feature encoder module, a data domain classification module, a supervised comparative learning module and a multi-task classification module; then, a joint optimization loss function is constructed based on data field classification loss, supervised contrast learning loss and task classification loss, and a gradient descent algorithm is adopted to train and optimize the cross-domain voice classification model based on the cross-domain voice classification data set and the joint optimization loss function; and finally, inputting to-be-classified voice into the trained cross-domain voice classification model to obtain a voice corresponding category. The discrimination ability and generalization ability of the model in a cross-domain scene are significantly improved, so that the model still maintains high classification precision in a complex multi-source voice environment.

The invention discloses a message extraction method and device, a servo system, a storage medium and a computer program product, and the method comprises the steps: capturing an interaction message between a motion controller and a servo driver, and obtaining initial message data; screening the initial message data, and retaining a communication message between the motion controller and the servo driver; performing format conversion on the screened initial message data to obtain analyzable message data; extracting data fields from the analyzable message data, wherein the data fields reflect information of instruction transmission, operation feedback and fault states between the motion controller and the servo driver; and performing format processing on the data field, and displaying the data field after format processing in a visual form. According to the scheme, efficient extraction, presentation and real-time monitoring of the message are realized by capturing the interactive message and performing screening, format conversion, data field extraction, format processing and visual display, and the debugging efficiency and troubleshooting speed of the servo system are improved.

An approach is provided for large language model (LLM) map feedback reporting. The approach involves, for example, processing an input specifying a map error / feedback using an LLM to classify a map error type. The approach also comprises determining a map error template based on the map error type that specifies structured data fields for the map error type. The approach further involves using the template to construct prompts for the LLM to generate questions to collect data items for populating the data fields, and providing the prompts to the LLM to generate the questions and collect the data items from the user. The approach further involves using template to generate additional prompts to generate a map error report of the data items in a structured data format, and providing the additional prompts to the LLM to generate the map error report for transmission to a map feedback system.

The embodiment of the invention provides an emergency data quality control analysis method and device based on big data. Wherein a microcirculation dynamic mapping model with time-space correlation is constructed and integrated through a nanofiber sensing array of the flexible electronic skin device. And performing time reference synchronous compensation and space coordinate transformation mapping on the model and spatio-temporal data of emergency treatment monitoring equipment to form a fusion data field, thereby realizing joint feature distribution of microcirculation parameters and emergency treatment parameters. The fused data field is subjected to mode coupling verification with a microcirculation compensation track map in a shock compensation mode feature library through a dynamic quality control engine, and when it is detected that mode mismatching exists between a parameter evolution path and a historical track, space-time signal fragments are reconstructed based on phase features and space distortion features; and generating a quality control report associated with the abnormal skin perfusion gradient node. According to the technical scheme provided by the embodiment of the invention, the quality control effect of the emergency data of the shock patient is improved.

The invention relates to the technical field of computer programming, in particular to a method for realizing data binding and code generation based on a Qt plug-in technology, which comprises the following steps: developing a Qt Creator extension plug-in, realizing dynamic loading and registration, analyzing a database file through the plug-in, generating a visual data view, and providing a visual binding interface through the steps. The method comprises the following steps: establishing a binding relationship between an interface control and a data source by supporting a dragging operation, automatically generating a JSON data model, compiling to generate a binding code according to the JSON data model, registering, and finally realizing code increment updating through file hash value comparison; according to the method, through the IDE integrated graphical interface, dragging connection of the control and the data field is supported, manual writing of repetitive codes is avoided, change is detected through the file hash value, only influenced codes are regenerated, compiling time is shortened, development efficiency is remarkably improved, and labor cost is reduced.

Proposed are a method and a device for receiving a PPDU by combining an RU or an MRU in a particular channel with an RU or an MRU in a neighboring 20 MHz channel in a wireless LAN system. Specifically, a reception STA receives a PPDU from a transmission STA. The reception STA decodes the PPDU to obtain control information. The reception STA decodes a data field of the PPDU on the basis of the control information. The control information comprises first or second information for an RU or an MRU in the bandwidth of the PPDU.

The invention relates to a medical image file processing method and device and electronic equipment, and the method comprises the steps: obtaining a series of DICOM files; according to the metadata of each DICOM file, shared data and non-shared data of each DICOM file are determined, and the metadata of each DICOM file comprises patient information, equipment parameter information and spatial position information corresponding to the corresponding slice image; combining the non-shared data of each DICOM file to obtain combined non-shared data, and storing the shared data and the combined non-shared data in a first metadata field; pixel metadata corresponding to each slice image is stored in a second metadata field, and the pixel metadata comprises a gray slope, an intercept, a window width and a window level; merging the pixel data corresponding to each slice image, and storing the merged image data in an image data field; and combining the first metadata field, the second metadata field and the image data field to generate a medical image file.

The invention relates to the technical field of engineering cost, and discloses a data entry method for engineering cost software, which comprises the following steps of: S1, importing an engineering quantity list file in an Excel format through an interface of the engineering cost software, and automatically analyzing a data structure of the engineering quantity list file; s2, based on a preset intelligent matching algorithm, performing dynamic mapping on the Excel data field and a data field of a project cost software function module; s3, adopting a data type self-adaptive rule to automatically classify and convert numerical values, texts and compound data in the Excel; s4, based on a data association generation algorithm, automatically establishing a hierarchical relationship and a dependency relationship between the engineering quantity list items; s5, executing one-button data import, and writing the processed structured data into a project cost software database in batches; according to the method, high-precision automatic mapping of the Excel field and the software module is realized through an intelligent matching algorithm and a dynamic weight adjustment mechanism based on the feature vector similarity, the matching accuracy is greatly improved, and the manual correction frequency is greatly reduced.

A system and method for applying a unified security policy across a technology stack, includes detecting a cloud object in a first cloud computing environment, the cloud object including a plurality of attributes, each attribute having a corresponding value; detecting a node in a security graph having a data field value which matches an attribute value of the cloud object, wherein the security graph includes a representation of a cloud environment; applying a policy based on the data field value to the detected cloud object; and applying the policy to another cloud object in a second cloud computing environment, in response to determining that a node representing the cloud object in the security graph is connected to a node representing the another cloud object.

The invention provides an enterprise-level application rapid development and deployment method and system based on model driving, and relates to the technical field of data processing, the method comprises the following steps: obtaining structured modeling data, carrying out semantic disassembly and relationship classification, and constructing an intermediate model structure; performing traversal analysis on the flow path to generate an execution mapping configuration table; extracting a form type, a data field definition and subsequent flow path information corresponding to each flow node, and matching and generating a front-end rendering component file and a rear-end interface description file in combination with a preset front-end template library and a service interface template; automatically splicing the front-end page code and the rear-end controller code by using a template engine to generate a target deployment structure; executing code construction and dependent compilation operation, and outputting a deployment package file conforming to enterprise-level application specifications; according to the method, the autonomy and the accuracy of rapid development and deployment of enterprise-level applications are improved.

The invention discloses a karst stratum tunnel disaster sensing method and system based on multi-source information, and belongs to the technical field of tunnel engineering safety monitoring, and the method comprises the steps: building a monitoring index data set, converging the monitoring index data set to a cloud end, carrying out the time-space registration, and generating a multi-dimensional time sequence data field; calculating data uncertainty of each monitoring area by adopting an information entropy theory, calculating spatio-temporal evolution characteristics, and performing classifier identification by combining a deformation field space gradient to obtain a key monitoring area; adaptively adjusting the acquisition frequency of the sensor, and starting supplementary monitoring equipment for encrypted observation; performing space-time response calculation by adopting a machine learning algorithm to generate a tunnel disaster evolution prediction result; and carrying out grading threshold comparison and numerical simulation verification on the prediction result to realize effective identification and perception of the disaster evolution state. According to the method, the technical means of combining multi-source data fusion, the information entropy theory, machine learning and self-adaptive monitoring is adopted, and dynamic, accurate and predictive perception of the tunnel disaster evolution process can be achieved.

The invention discloses a data transaction security assessment method and system, and relates to the technical field of data security and intelligent assessment. The method comprises the steps of performing feature analysis on a data field, determining a sensitivity weight and generating a sensitivity vector; the fields are graded according to the sensitivity vectors, and dynamic adjustment is carried out in combination with transaction related information to obtain a grading result; calculating a data content risk, a field association risk, and a transaction environment risk based on the sensitivity feature set; determining a weight according to a transaction scene, and weighting various risks to obtain a comprehensive score; and judging the risk level according to the comprehensive score and a threshold value dynamically determined based on historical data. According to the invention, through hierarchical sensitivity modeling and dynamic risk calculation, fine-grained security assessment of different types and sensitivity data is realized, and the risk result can be adaptively adjusted along with changes of data contents, transmission paths and transaction environments, so that the accuracy, real-time performance and scene adaptability of assessment are improved, and the risk assessment efficiency is improved. The defects of a static evaluation method in the prior art are overcome.

The invention provides a webpage analysis code generation method, device and equipment based on a large language model, and relates to the technical field of natural language processing, webpage analysis and the like. The method comprises the following steps: determining a key information field according to a demand text of a webpage analysis task through a first large language model, and filling the key information field into a structured analysis prompt template to obtain an analysis prompt text; the key information field comprises at least one of the following items: a domain name of a target website, a target webpage type, a target webpage structure and a target data field; and through a second large language model, generating an analysis code of the webpage analysis task according to the analysis prompt text.

The invention relates to the field of user interface design, in particular to a table generation and optimization method and device based on demand analysis, and the method comprises the steps: receiving demand data inputted by a user, and recognizing the attributes of a table, data entities and the relation between the data entities according to the demand data; generating a table structure according to the data entity and the attribute; according to the data entities and the relation between the data entities, target demand parameters are matched, and the target demand parameters comprise data fields and constraint conditions; based on a matching result, filling a table structure with the target demand parameter to obtain an initial table; obtaining an interaction behavior of the user on the initial table in real time, and analyzing demand change data of the user according to the interaction behavior; and updating the initial table based on the demand change data. By analyzing the interaction behavior and demand change of the user, the system can continuously optimize and adjust the table in the use process, so that the table can be automatically adjusted along with the demand change.