1962 results about "Data field" patented technology

A system and method for machine learning-based data field validation is proposed that utilizes a specific trained machine learning model data architecture that is adapted to be more resilient against training set class imbalance, using a Siamese triplet LSTM network architecture that uses three LSTMs that are trained together and operate in concert. An example non-limiting practical use includes using the Siamese triplet LSTM network architecture to validate whether free-text data fields include a single jurisdiction in an address or multiple jurisdictions in the address.

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.

A computer implemented method, system and non-transitory computer-readable device for a remote deposit environment. Upon receiving a user request, based on interactions with the UI, the method implements an electronic deposit of a financial instrument by activating a camera on the client device to generate a live stream of image data of a field of view of at least one camera, wherein the live stream includes imagery of at least a portion of the financial instrument. The method continues by extracting in real-time, based on the formation of byte array objects from the live stream of image data, data fields from a ranked sequence of imagery to be processed by an optical character recognition (OCR) program resident on the client device. The OCR process extracts one or more data fields from of the financial instrument that are communicated to a remote deposit server to complete the electronic deposit.

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 relates to the technical field of data processing, and discloses a virtual volume scanning data generation method and system for a radar data stream. The method comprises the following steps: performing multi-dimensional decomposition and parallel preprocessing on an obtained original radar data stream to obtain a multi-channel preprocessed data stream; carrying out adaptive feature extraction and dynamic clustering on the multi-channel preprocessed data stream to obtain a time-varying feature cluster; constructing a reconfigurable virtual scanning structure based on the time-varying feature cluster to obtain a self-optimization scanning mode; performing multi-level spatial interpolation and phase reconstruction on the time-varying feature cluster through a self-optimization scanning mode to obtain a preliminary virtual volume scanning data field; performing target feature enhancement and multi-source environment information fusion on the preliminary virtual volume scanning data field to obtain high-simulation virtual volume scanning data; and performing multi-dimensional consistency verification and intelligent format adaptation on the high-simulation virtual volume scanning data to obtain target virtual volume scanning data. According to the method and the device, the efficiency and the accuracy of generating the virtual volume scanning data for the radar data stream are improved.

The invention discloses a financial data automatic filling method and device, equipment and a storage medium, and belongs to the technical field of big data. The method comprises the following steps: determining a data source corresponding to original financial data by using a pre-trained data classification model; acquiring a data processing rule engine and a target data filling template matched with the data source; performing data cleaning on the original financial data based on a data cleaning rule; performing data analysis on the standardized data by using a data analysis rule; performing association relation extraction on the target data source field and the target filling field by using a data mapping rule, and performing data field mapping according to the field association relation; and according to a data field mapping result, filling the target data source field into the target data filling template to generate a financial data report. The invention further relates to the technical field of block chains, and financial data are stored on the block chain nodes. According to the method and the device, the applicability and the operation convenience of automatic filling and reporting of financial data in a multi-source data scene are improved.

Disclosed herein are system, apparatus, device, method and / or computer program product embodiments for providing a mid-stream deposit availability schedule to a customer electronically depositing a check. The deposit availability schedule is generated by activating a mobile financial application, receiving a customer request to deposit a financial instrument, and based on the customer request, activating a camera on the client mobile device to access a field of view of at least one camera and capture one or more images of a financial instrument, store, in a computer memory on the client mobile device, the one or more images. An optical character recognition program, resident on the client mobile device, extracts in real-time, one or more data fields from one or more portions of the financial instrument, communicates the one or more data fields to a remote deposit server and receives a deposit availability schedule, before acceptance of the remote deposit.

A method generates data analysis templates. A computing device receives, via a graphical user interface, a natural language input, which includes multiple terms. The terms include one or more data fields and / or data values from a data source. The device designates the natural language input as trigger text for a data analysis template. The trigger text includes the multiple terms. A user defines one or more rules for a subset of the terms, each rule specifying respective criteria to match a respective term in the subset. A user specifies multiple data visualizations corresponding to the trigger text. Each of the data visualizations (i) uses a respective one or more data fields, from the data source, corresponding to terms from the trigger text and (ii) has a respective data visualization type. The device generates the data analysis template according to the trigger text, the user definition, and the user specification.

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.

The invention relates to the technical field of data sharing, and particularly discloses an electrical equipment supply chain data security access method and system, and the system can intelligently match table structure information in a power industry database based on natural language input of a user, and generates a corresponding SQL query. By combining a natural language processing technology with a large language model, a user can easily access and query required power industry data under the condition that a complex SQL statement or a database structure does not need to be mastered. According to the method, the efficient query task can be automatically generated, the data access difficulty is greatly reduced, meanwhile, a data field level encryption scheme and a user permission intelligent verification mechanism are designed, and the safety of the data access sharing process is ensured; and the method has good expansibility and can be compatible with power enterprise databases of different scales.

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 provides an Internet of Things protocol automatic identification system and method based on a data model, and relates to the technical field of Internet of Things protocol identification. The method comprises the following steps: performing data analysis on a communication data packet, extracting a protocol head feature, a data field feature and a time pattern feature of the communication data packet, generating an Internet of Things protocol feature, and performing protocol analysis on the Internet of Things protocol feature according to a first protocol identification model to obtain a first protocol identification result; acquiring transmission state monitoring data of the Internet of Things equipment about the communication data packet, extracting Internet of Things transmission characteristics of the communication data packet from the transmission state monitoring data, and performing transmission analysis on the Internet of Things transmission characteristics according to a second protocol identification model to obtain a second protocol identification result; and determining a protocol analysis list according to the first protocol identification result and the second protocol identification result, and performing data analysis on the communication data packet based on a plurality of analyzers in the protocol analysis list. According to the invention, the accuracy of automatic identification of the Internet of Things protocol is improved.

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.

A patient data charting device configured to automatically capture electronic patient care record (ePCR) data from a caregiver is provided. The device includes a memory storing an ePCR including a plurality of data fields, an output device, a microphone configured to acquire speech, and a processor. The processor is configured to convert the speech to text, identify a first value of a data field of the plurality of data fields based on the text, populate the first data field with the first value, generate a prompt that requests a second value of a second data field of the plurality of data fields based on the first data field, and present the prompt to the caregiver via the output device.

Methods and systems for secure, federated, and decentralized ownership, storage, sharing and usage of big data are provided. According to one example, a first server maintains access to a plurality of federated data sources including at least one local database and at least one remote database. The local database is subject to a first data policy controlled by the first server and the remote database is subject to a second data policy controlled by a remote server. The first server receives a query from a user electronic device and verifies at least one permission attribute of the user electronic device relative to the data policies. After the federated data operation query has been approved, the first server generates results of the query including data fields from the local and remote databases in compliance with the first and second data policies.

A computer-implemented method for automated data record resolution includes: receiving an unmapped data record comprising a plurality of data fields, wherein at least one data field of the plurality of data fields causes a mapping error between the unmapped data record and a plurality of validated data records; generating, from the plurality of validated records, a resolution candidate record for the unmapped data record based on detecting the mapping error between the unmapped data record and the plurality of validated data records; and automatically re-assigning one or more data records of the computer database that are digitally associated with the unmapped data record to the resolution candidate record.

The invention discloses a data processing method and device, electronic equipment and a nonvolatile storage medium. The method comprises the steps that a user demand text is obtained, an initial cue word corresponding to the user demand text is determined, and the initial cue word comprises initial metadata information; standard metadata information corresponding to the initial metadata information in a metadata vector library is determined; according to the standard metadata information, adjusting the initial cue word to obtain a target cue word; the target cue word is analyzed through a large language model, a task script is obtained, data in the data field is extracted, converted and loaded by executing the task script, and the task script is used for meeting the requirement corresponding to the user requirement text. According to the data synchronization method and device, the technical problem that the data synchronization efficiency is low due to the fact that a large amount of parameter configuration needs to be manually carried out in the scheme of carrying out extraction, conversion and loading processing on the data in related technologies is solved.

Proposed are a method and device for receiving a PPDU in a wireless LAN system. Specifically, a reception STA receives a PPDU through a wide band from a transmission STA, and decodes the PPDU. The wide band is a 320 / 160+160 MHz band configured from a first band and a second band. When the first band is an 80 MHz band in which puncturing is performed in units of 20 MHz, the first band includes a first RU which is an aggregate of a 484RU and a 242RU. The second band is a 240 MHz band excluding the first band in the wide band, and includes a second RU which is an aggregate of three 996 RUs. The PPDU includes a control field and a data field. The data field is received via a first multi-RU which is an aggregate of the first and second RUs.

A system for stable and streamlined transaction approval includes a rule management server and an authorizer server. The rule management server is configured to receive a transaction rule that includes a list of named entities specified by a client. The rule management server stores past transaction data and analyzes patterns in the past data to determine a named entity identification rule. The authorizer server receives a transaction data payload related to a pending transaction associated with the client and identifies a noisy data field in the transaction data payload. The noisy data field includes a representation of a particular named entity and one or more irrelevant strings. The authorizer server parses the particular named entity based on the named entity identification rule and determines whether the particular named entity is one of the named entities in the list. The authorizer server conducts a transaction evaluation using the result.

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.