7214 results about "Datasheet" patented technology

In some examples, computer-implemented systems and processes deploy securely de-risked elements of confidential data within a distributed computing environment. For example, an apparatus may obtain configuration data associated with a source data table. The configuration data may specify an identifier of a column of the source data table that includes elements of confidential data, and based on the configuration data, the apparatus perform operations that anonymize the elements of confidential data within the column of the source data table and generate an anonymized column within the source data table. The apparatus may also perform operations that provision an anonymized data table that includes the anonymized column to at least one computing system, which may process the anonymized data table and generate an output data table that includes the anonymized column and maintains a referential integrity between the source data table and the output data table.

In some examples, computer-implemented systems and processes deploy securely de-risked elements of confidential data within a distributed computing environment. For example, an apparatus may obtain configuration data associated with a source data table. The configuration data may specify an identifier of a column of the source data table that includes elements of confidential data, and based on the configuration data, the apparatus perform operations that anonymize the elements of confidential data within the column of the source data table and generate an anonymized column within the source data table. The apparatus may also perform operations that provision an anonymized data table that includes the anonymized column to at least one computing system, which may process the anonymized data table and generate an output data table that includes the anonymized column and maintains a referential integrity between the source data table and the output data table.

An analysis engine receives data characterizing a prompt for ingestion by a generative artificial intelligence (GenAI) model. The analysis engine, using a prompt injection classifier determines whether the prompt comprises or is indicative of malicious content or otherwise elicits malicious actions. Data characterizing the determination is provided to a consuming application or process. Related apparatus, systems, techniques and articles are also described.

The invention discloses a data quality monitoring method and system based on a knowledge graph. According to the method, data tables and fields in multi-source heterogeneous data are constructed into graph nodes, graph edges are constructed through main and foreign key constraint relationships and field value overlapping analysis, and a data blood relationship knowledge graph is formed; business rules are coded into the atlas to execute data constraint check, and an abnormal data influence range is traversed and tracked through a directed graph; and dynamic monitoring is realized based on the time change of the abnormal score sequence. The invention further provides system implementation including data acquisition and preprocessing, knowledge graph construction, quality monitoring, problem diagnosis and quality evaluation. The method solves the problems that a traditional method is difficult to track the influence range of abnormal data and lacks systematic evaluation, and improves the automation level and accuracy of data quality management.

An orchestration component implemented within a cybersecurity system and operating in concert with a cybersecurity appliance to enhance cyber threat detection or a response to a cyber threat detected by the cybersecurity appliance is described. The orchestration component comprises a first landscape analysis module, a data score and an action severely configured to operate with a first large language model to (i) analyze threat landscape data received from one or more external sources and (ii) identify threat technique data associated with one or more cyber threats included within the threat landscape data. The orchestration component further comprises a data store adapted to maintain the threat technique data identified by the threat landscape analysis module; and an action severity module is configured to adjust a sensitivity of a cyber threat detection engine of the cybersecurity appliance in monitoring for the one or more cyber threats represented by the threat technique data.

The invention provides a supply chain collaborative material management system and method, and relates to the technical field of material management, and the method comprises the steps: receiving a multi-enterprise heterogeneous material data flow, and constructing an industry knowledge graph based on the field-level semantic mapping of a dynamic ontology library; a standardized data table is generated; standardized data is injected into a distributed message queue for parallel processing, dynamic cache partitions are created according to material object labels, timestamp indexes are built in the dynamic cache partitions, a sliding window mechanism is adopted to scan data, and multi-strategy resolution is performed on conflict data in a window; performing conjoint analysis on the cleaned data to generate an enhanced analysis report, and activating a case transfer learning mechanism to update a model when the similarity between new data and historical cases exceeds a threshold value; constructing a material state transfer matrix for the abnormal data, simulating a correction operation in a digital twin environment, and triggering automatic correction; the problems of multi-enterprise heterogeneous data integration, dynamic data processing, intelligent analysis and the like are solved, and the collaboration efficiency and the management level of a supply chain are improved.

The embodiment of the invention discloses an intelligent contract auditing method and device based on a multi-modal large model and a medium, and relates to the technical field of contract auditing, the method comprises the steps that a to-be-audited target contract document is acquired, multi-modal data in the target contract document is analyzed, and the multi-modal data comprises text data, table data and image data; performing feature extraction on the multi-modal data to obtain multi-modal feature data, mapping the multi-modal feature data to a unified dimension space so as to calculate an association weight between each modality through a cross-modal attention mechanism, establishing cross-modal bidirectional link data, and obtaining multi-modal data; the multi-modal feature data comprises any one or more of text semantic features, table relation maps and image visual features; and based on the multi-modal feature data and the cross-modal bidirectional link data, performing single-modal self-consistency verification and cross-modal contradiction detection on the target contract document to generate auditing information of the target contract document.

The invention relates to the technical field of intelligent manufacturing, discloses a papermaking equipment fault tracing method and system based on a process knowledge graph, and discloses the papermaking equipment fault tracing method and system based on the process knowledge graph. The method and the system comprise data acquisition and preprocessing, papermaking process knowledge graph construction, fault event detection and matching, fault tracing and propagation path reasoning, and maintenance scheme recommendation and optimization. The method overcomes the limitation that the traditional method is difficult to capture the cross-equipment, cross-process and cross-time sequence deep causal association and fault propagation path of the papermaking equipment. By constructing a comprehensive papermaking process knowledge graph, equipment operation state data, process parameter data, production quality data, equipment structure principle, process flow knowledge, fault mode knowledge, maintenance experience and other heterogeneous knowledge are subjected to deep fusion and semantic association, so that the system can exceed the correlation of the data surface; and an internal mechanism and a propagation chain of the fault are deeply excavated.

The invention provides a method for generating an SQL (Structured Query Language) by a natural language based on bidirectional mapping and semantic parsing, which relates to the technical field of database query and comprises the following steps of: extracting natural language query elements and packaging the natural language query elements into structured data, and establishing a mapping relationship from a query field to a service attribute and a physical data table by adopting a bidirectional Hash index technology; and automatically identifying multi-table association keys, performing semantic extension and compliance verification, generating an abstract syntax tree, performing processing according to user permission, and finally converting the abstract syntax tree into an SQL statement conforming to a target database syntax specification. According to the method, the accuracy and the efficiency of converting the natural language into the SQL are improved, and the flexibility and the safety of the system are enhanced.

The invention provides an integrated metadata management method and system based on data source expandability, and relates to the technical field of data sources, and the method comprises the steps: executing real-time detection on a plurality of heterogeneous data sources through a PF4J plug-in framework, collecting connection information, and establishing a dynamic connection pool; obtaining a table structure, a field attribute and an association relationship list, and assembling the table structure, the field attribute and the association relationship list into JSON format data; performing analysis and standardization processing on the data, and constructing an association degree calculation matrix; generating a standardized data structure description file; establishing a three-layer index directory, and detecting structure change and updating; and calculating a data table reference dependency relationship, and generating a DAG data flow path. According to the method, efficient integration and management of heterogeneous data sources are realized, and the metadata processing efficiency is improved.

The invention relates to the technical field of data information processing, in particular to an artificial intelligence-based index layer model construction analysis method and system, and the method comprises the following steps: 1, multi-source data synchronization and quality evaluation; 2, service context analysis and subject domain intelligent division are carried out, and service document and data table field semantics are analyzed; 3, index demand intelligent analysis and calculation logic generation: analyzing index demands input by a user through a natural language processing technology, matching service entities in the knowledge graph, generating initial calculation logic and optimizing execution efficiency; and 4, dynamically updating the index data and verifying the consistency, executing the optimized computational logic to generate the index data, tracking the blood relationship of the data, triggering dynamic updating, and setting a threshold value according to a historical fluctuation range to carry out abnormal alarm. Through automatic and intelligent processing, the probability of human intervention and human errors is reduced, and the efficiency and accuracy of data processing are improved.

The invention provides a business process construction method combining a workflow engine and a dynamic form, which relates to the technical field of low-code platforms, and comprises the following steps of: establishing a data table according to a business, selecting and importing the data table in a code generation module, generating a basic code package, re-operating a main program compiling code package and loading the code package to a JVM (Java Virtual Machine) operating environment; creating a dynamic form on the basis of the entity class information of the code package through a visual form designer of the dynamic form module, and outputting dynamic form configuration in a JSON (JavaScript Object Notation) format; according to the method, the dynamic form and the process engine are combined, highly flexible business process design can be realized, a user can dynamically design the form and the process model as required to meet different business requirements, and the user-defined component can be designed according to a business data structure and common functions, so that the form can better adapt to a specific business scene, and the user experience is improved. And the user experience and the working efficiency are improved.

Various embodiments relate to a method and related device and machine-readable storage medium including one or more of the following: receiving, via a first user interface scene, a user specification of a physical structure; committing a data representation of the physical structure to a digital twin; transmitting the digital twin to a remote device; receiving an update to the digital twin from the remote device, producing an updated digital twin; and rendering, via a second user interface scene, a graphical representation of the updated digital twin.

The invention discloses a multi-table combined natural language query SQL (structured query language) generation method, which comprises the following steps of: 1, constructing a database meta-knowledge graph, and establishing a triple storage comprising a table structure, a primary and foreign key relationship and business description for each data table; 2, receiving a natural language query request, and calculating the topic relevancy between query semantics and each database table through a pre-trained topic matching model; 3, dynamically constructing a view, and logically associating the database tables of which the theme relevancy exceeds a threshold value to form a temporary view; 4, generating a context enhancement prompt, and combining the temporary view structure, the field semantic description of the view and the view content sample to form a structured prompt; 5, inputting the natural language query and the structured prompt into the large language model to generate candidate SQL statements; and step 6, executing verification and iterative optimization on the candidate SQL statements, verifying logic correctness through SQL execution plan analysis and result sampling, and triggering and prompting a reconstruction mechanism when detection is abnormal.

The embodiment of the invention provides a knowledge base construction method, a data processing method, equipment, a storage medium and a program product. The method comprises the following steps: generating table description information of a data table in database data and field description of the data table based on the database data and document data; identifying table relation information corresponding to the data table from historical query statements of the database data; therefore, the asset knowledge base can be constructed based on the table description information, the field description information and the table relation information, the table description information and the field description information are generated not only based on the database data, but also based on the document data, and the table relation information is recognized and obtained from the table description information and the field description information in combination with the historical query statements and the document data. Therefore, the information in the constructed asset knowledge base is rich and available, and the data quality of the asset knowledge base is improved.

The invention provides a distributed storage and data warehouse permission synchronization method and system, and relates to the technical field of permission management, and the method comprises the steps: analyzing user operation data of distributed storage, training a machine learning model, and generating a directory permission intelligent mapping table; analyzing the structure information of the data table in the data warehouse, and generating a multi-dimensional table authority evaluation model; generating a self-adaptive permission rule base by combining the two, and deploying the self-adaptive permission rule base to each node of distributed storage; when the permission is changed, the system calculates an influence range according to the self-adaptive permission rule base and generates a permission updating instruction sequence; and the system monitors the instruction execution state, identifies abnormal nodes, and performs repair based on the permission propagation tree to ensure the permission consistency. According to the method, automatic synchronization of distributed storage and data warehouse authority can be realized, the authority management efficiency is improved, the manual intervention cost is reduced, and the data security is enhanced.

The invention discloses a method and a device for adaptively generating a structural query statement by using a natural language. The method comprises the following steps: acquiring a natural language query statement input by a user; vectorizing the natural language query statement to obtain a first query statement and a data table and an SQL statement corresponding to the first query statement; rewriting the natural language query statement to obtain a second query statement; recalling a candidate data table and a candidate table field based on the second query statement and a preset to-be-queried data table; the first input data and the first sample data are input into the preset large language model, the query statement and the reasoning chain are structured, the natural language query statement input by the user is corrected, the difference between the natural language query statement and the database table structure is reduced, and the accuracy of data table recall is improved; by recalling the candidate data table, the reasoning difficulty is reduced, so that the accuracy of generating the structured query statement according to the natural language query statement is improved.

A method may include accessing data associated with a failure of a 5G network component. The method may include providing the data associated with the failure of the 5G network component to a first machine learning model, configured to determine and output data indicating a root cause of the failure. The method may include providing data indicating the root cause of the failure to a second machine learning model, configured to determine and output data indicating one or more service providers and respective destinations associated with the root cause. The method may include generating a service ticket may include data indicating the root cause and the respective destinations associated with the root cause. The method may include transmitting the service ticket to the respective destinations of the one or more service providers associated with the root cause of the failure.

The invention discloses a hyper-converged server resource pooling method and system, and belongs to the technical field of resource scheduling, and the method comprises the steps: collecting spatial information, generating a multi-dimensional resource topological graph, abstracting edge node and core node resources into virtual units with position labels, constructing a virtual resource pool, and generating a three-dimensional metadata table; constructing an independent double-queue architecture, configuring a token bucket, triggering a queue clearing mechanism based on a control period, and performing micro-batch merging on edge node short transactions; binding adjacent virtual units by taking the physical position of the equipment as a fragmentation primary key, monitoring cross-virtual unit access traffic, migrating a high-frequency data copy and redirecting a write request, and adjusting fragmentation granularity according to data relevance; the virtual unit closest to the equipment group is selected as a main node in the data fragments, write operations are combined, low-delay paths are selected for synchronization, an asynchronous confirmation mechanism is adopted to respond to edge nodes, the local resource hit rate and the task processing efficiency are improved, and the real-time performance and reliability of industrial control are guaranteed.

The invention relates to the technical field of vibration monitoring, in particular to a slurry pump motion monitoring management system based on data analysis, which comprises a multi-source acquisition module, a period judgment module, a trend focusing module and a dynamic management and control module. According to the method, vibration data are collected through a three-axis acceleration sensor, a fundamental frequency amplitude is extracted through FFT, time-frequency characteristics and periodic distribution are fused in combination with an extreme value interval sequence, the data representation dimension is enhanced, the rising slope is processed through moving average, the periodic variation is calculated, random noise is restrained, and trend continuity is enhanced. Monotonicity test is combined with dynamic threshold judgment to improve anomaly recognition sensitivity; a sliding window is used for segmenting multi-cycle data; a sudden change interval is positioned based on a pressure amplification rate second derivative; the limitation of a frequency domain on transient feature recognition is broken through, a pressure amplification rate three-dimensional vector is constructed, cosine similarity is calculated, and a working condition difference degree is quantified to dynamically bind a maintenance instruction; and closed-loop feedback is formed to improve the early warning and decision matching degree.

Disclosed in embodiments of the present application are a method and apparatus for acquiring lineage data, a computer device, and a readable storage medium. The method comprises: obtaining lineage information of a real-time generation task and data information of a dependency relationship between the real-time generation task and a predecessor task thereof, the lineage information comprising at least two among identification information of the real-time generation task, a data input database table, a data output database table, an output relationship, and an input relationship, and the data information comprising at least two among identification information of the predecessor task, status, and a first run time; writing the lineage information and the data information into message middleware, and processing the lineage information and the data information in the message middleware, and obtaining a lineage map and an index map of the real-time generation task; and uploading the lineage map and the index map to a graph database and an index database, respectively. In the present application, comprehensive acquisition of lineage data can be implemented, so that impact analysis can be carried out on a data table in a lineage map.

The invention discloses a self-adaptive SQL differential privacy noise adding method, and relates to the technical field of data protection. In order to accurately calculate and add noise of a proper magnitude in a complex SQL statement, the adopted scheme comprises the following steps: regularly collecting and updating metadata of a database, analyzing attribute features of a data table, and forming a data attribute feature library and a corresponding data sensitivity library; the SQL query request is rewritten into an abstract syntax tree and traversed, and an aggregation function, multi-table connection and a sub-query structure are recorded; key semantic information contained in the request is bound with the data sensitivity library, the sensitivity of the request is calculated, and a privacy budget is distributed in a self-adaptive mode; the privacy budget allowance is checked, when the allowance is sufficient, a data disturbance mechanism meeting-differential privacy is used for disturbing the query result, a disturbed result is obtained, and otherwise, the request is rejected. The method is used for accurately calculating the dynamic allocation privacy budget according to the characteristics of the complex SQL query.

A database system is operable to perform a power supply strategy selection function based on first energy utilization-based operation optimizer input data to generate first energy utilization-based power supply strategy data denoting, for each power supply type of a plurality of power supply types, a corresponding first proportion of power supply resources that be implemented as the each power supply type. A first set of power supply resources is selected to execute a first database operation based on the first energy utilization-based power supply strategy data. The first set of power supply resources are utilized to power a first set of computing devices to enable the first set of computing devices to participate in execution of the first database operation in accordance with the first energy utilization-based power supply strategy data.

The invention provides an industrial data online migration method, medium and system of a productivity middle platform, and belongs to the technical field of electrical digital data processing.The method comprises the steps that firstly, historical access records of an industrial data source are collected, and a deep neural network model comprising a multi-head attention layer, a time sequence feature extraction layer and a residual connection layer is constructed; and the prediction of the data change rate is realized. And based on a prediction result, dynamically calculating a data change rate demarcation point by utilizing an optimization equation set, and dividing a data table into different change frequency categories. And then constructing a data dependency relationship matrix, and determining a migration sequence by adopting an improved topological sorting algorithm. Batch migration, incremental migration and real-time synchronization mechanisms are adopted for different types of data, and model updating is triggered through real-time monitoring, so that dynamic optimization of a migration strategy is ensured. Finally, data consistency verification is carried out, migration accuracy is guaranteed, and the technical problem that the online migration efficiency of industrial data is low due to real-time dynamic change of the data change rate is solved.

Systems and methods for distributed order fulfillment are disclosed. Real-time fulfillment data indicating unavailability of a first item identified in an order is received from a first computing device. The real-time fulfillment data is generated in response to an input received by the first computing device. Order update data indicating unavailability of the first item and one or more substitute items is transmitted to a second computing device. The order update data causes the second computing device to generate an interface including the substitute items and a portion of the order update data. A substitute response from the second computing device. In response to receiving the substitute response, The selected substitute item is substituted in place of the first item during fulfillment when the substitute response indicates acceptance the substitute item and the first item is removed from the order when the substitute response indicates rejection of the substitute items.

The invention discloses a data warehouse intelligent construction method and device based on a large model. The invention provides a data warehouse intelligent construction method and device based on a large model, and belongs to the technical field of big data processing. The method comprises the following steps: a user registers to-be-collected business system data source information through a data source registration entry, and submits the information as a data processing task; receiving a data processing task through a task executor, calling a large model to carry out feature analysis on a data table, and identifying a table type, a service attribute and an acquisition parameter; executing data acquisition according to an analysis result, including identifying a temporary table, determining an acquisition period, selecting an increment field and the like; performing intelligent exploration on the collected data, and identifying field features and data quality; performing data conversion based on the probing result, wherein the data conversion comprises automatically binding a business rule, associating a data standard and generating a conversion rule; and finally, executing data fusion, intelligently matching the target table and the field mapping relation through a large model, generating a fusion rule, and executing fusion.

A method for AI-driven natural language search includes receiving a user query for one or more items from a user, processing the user query by searching against at least one relational database associated with the query, where the relational database is generated by extracting features from electronic documents of a plurality of items associated with the one or more items and by identifying specifications or respective values corresponding to the extracted features of the plurality of items, generating one or more query results based on the processing of the user query, where the one or more results include at least one item identified from the plurality of items and a justification for explaining an irrelevance of the at least one item, and transmitting the one or more query results to a user device for presentation to the user.

The invention relates to the field of data management and knowledge maps, and provides a civil administration data consanguinity knowledge map construction method and device based on a large model, and the method comprises the steps: constructing a basic entity network based on the metadata feature extraction of civil administration data; based on the basic entity network, analyzing the data table structure to generate a data table structure relation model; analyzing the complex structured query language statement, identifying field-level blood relationship, and generating a preliminary blood relationship graph; all physical source tables are traversed, virtual table redundancy and data node repetition are eliminated, and an optimized blood relationship graph is generated; and based on the optimized blood relationship graph, identifying public data nodes and combining field-level data blood relationships to generate a final civil administration data blood relationship graph. According to the method, the problems of difficulty in accurately analyzing complex SQL statements, processing virtual table redundancy and data node repetition in the prior art are solved, and high-precision and automatic civil administration data consanguinity knowledge graph construction is realized.

Methods and systems are provided for using a fine-tuned language model to reduce representations of structured data. In embodiments described herein, training data is accessed that includes structured data, a set of queries for the structured data, and each portion of the structured data that is relevant to each query of the set of queries. A language model is fine-tuned to maximize a cumulative reward based on the training data. The cumulative reward includes a reward for determining a correct portion of the structured data, a first penalty for failing to determine the correct portion of the structured data, and a second penalty for determining an incorrect portion of the structured data. The fine-tuned language model is then output.

The invention discloses an SQL (Structured Query Language) statement generation method and equipment based on a natural language and a medium, and the method comprises the following steps: constructing an RAG knowledge base and a data table knowledge graph of a project, then obtaining a to-be-converted natural language of the project, and performing keyword retrieval on the natural language through the RAG knowledge base to obtain an association table set; performing graph traversal on the natural language through the data table knowledge graph to obtain an associated node set; packaging the screening condition of the natural language to be converted, the association table set and the association node set to generate a context knowledge base of the natural language; and finally, according to the context knowledge base and the semantic conversion model, obtaining an SQL statement of a natural language. The problem of low efficiency of multi-table association path discovery is solved by constructing a dynamic extensible database relationship graph; a unified retrieval enhancement mechanism for the RAG knowledge base, the extensible knowledge graph and the historical query features is established, and the problem that target context retrieval is low in efficiency is solved.