346 results about "Query statement" patented technology

The application discloses a kind of intelligent query control method and electronic equipment based on natural language interaction.The method includes the following steps: building context knowledge base, converting into context vector, and storing in vector database;Convert the input natural language question into query vector;Retrieve the k context vectors most similar to the query vector from the vector database, and determine the corresponding context information;Combine the natural language question and the retrieved context information into a prompt word sequence input into a large language model (LLM) to obtain an SQL query statement, and analyze whether the natural language question contains a control intent;Execute the SQL query statement;If the natural language question contains a control intent, analyze the query result intelligently and perform the corresponding device control operation.The application can analyze the control intent in the natural language question, and after the result is queried, the corresponding device can be controlled according to the control intent to work, improving the work efficiency.

The application discloses a multi-user data association method and device based on a structured query language and an equipment. The method is through a first data set association clause in a SQL statement for associating data sets of multiple users; a data set association security operator is obtained which corresponds to a data set association operator and complies with a multi-party security calculation protocol; a data set association ciphertext execution plan of each user is generated according to the data set association security operator; the data set association ciphertext execution plan of the user is executed through a privacy calculation engine of the user; and the multiple data set association security operators in the multiple data set association ciphertext execution plans are used to associate the data sets of the multiple users in a privacy calculation manner. In this way, the plaintext execution plan of the multi-user data association clause in the SQL statement is rewritten into the ciphertext execution plan of each user, the multiple ciphertext execution plans perform cross-user joint data analysis in a privacy calculation manner, and the security of multi-party data can be effectively ensured.

This application relates to the field of fintech and discloses a dynamic hybrid parsing and deterministic verification system and method for fuzzy bond instructions. The system constructs structured data through an instruction preprocessing module; a routing decision module calculates complexity scores based on structure, semantics, and business characteristics, and generates path selection instructions using a resource-aware dual-threshold strategy; a hybrid parsing module responds to instructions, employing a rule engine to handle low-complexity tasks and a large-scale model with enhanced retrieval to handle highly ambiguous tasks; a fallback verification module performs confidence-weighted integration and logical consistency checks, and repairs anomalies through issuer set operations and edit distance matching; a mapping generation module constructs standard query statements using an abstract syntax tree; and a closed-loop optimization module dynamically updates parameters based on user interaction feedback. This invention effectively balances computational efficiency and parsing accuracy, eliminates model illusion risks, and achieves adaptive evolution of the system.

The application discloses a Text-to-SQL intelligent agent coordination system and method for perceiving potential intention of a user in a multi-round context. The system comprises a memory bank, a prompt strategy pool, a strategy recommender, an SQL generator, an SQL refiner and a strategy optimizer. The memory bank is used for storing system running data. The prompt strategy pool is used for storing prompt strategies. The strategy recommender is used for receiving user information and strategy information of the prompt strategies, identifying the current potential intention of the user based on the user information and the strategy information, and matching the optimal strategy from the prompt strategy pool according to the potential intention to constrain the generation of an SQL query statement. The SQL generator generates an SQL query statement based on the current natural language query of the user, the system running data and the optimal strategy. The SQL refiner is used for adjusting and iteratively updating the SQL query statement. The strategy optimizer is used for updating the prompt strategies. The application increases strategy selection before SQL generation, so that the SQL generator can generate an SQL statement meeting the user demand at one time with a higher probability, and the cost is reduced.

The embodiment of the specification provides a reinforcement learning method and device for a large language model. The method comprises: acquiring a base large language model with a thinking chain generation capability; driving the base large language model to generate a plurality of candidate replies for a target query statement, each candidate reply comprising thinking chain content and an answer; matching the thinking chain content in each candidate reply with a preset rule set in an artificial knowledge base, so as to determine the compliance degree of the thinking chain content with the rule set as a first reward value; determining a second reward value corresponding to the answer in the candidate reply; determining a comprehensive reward value of the candidate reply according to the first reward value and the second reward value; and updating parameters of the base large language model according to the comprehensive reward values corresponding to the plurality of candidate replies respectively. The thinking process of the model can be constrained, and the convergence speed of the model is improved.

This invention discloses a method, system, device, and medium for semantic correction and illusion suppression in power data queries, comprising: receiving colloquial power query text input by a user; correcting non-standard vocabulary through a dedicated power semantic correction network module; mapping the colloquial power query text to standard power terms; and generating standardized query statements; monitoring the average attention weight of historical output words in real time; determining that an attention black hole phenomenon has occurred when the average attention weight exceeds a preset threshold; recovering part of the attention weight from historical output words and redistributing it to visual words representing entities in the power knowledge graph in the input sequence; dynamically adjusting the intensity of attention redistribution according to the decoding progress; continuing to decode and generate standardized query statements based on the updated attention matrix; submitting the standardized query statements to the database execution engine for verification; and adding the query and generated query statements to the generated query set if the execution is successful.

This application relates to the field of information technology, specifically to a natural language query method and system based on a low-code platform. The method includes the following steps: reading the creation context of a data table and fields on the low-code platform, and generating a related thesaurus of the data table and fields based on the creation context; receiving a natural language query statement input by a user, extracting the action words and predicate words of the natural language query statement to obtain the user's query intent; comparing the predicate words with the related thesaurus to obtain matching related words; replacing the corresponding predicate words with the matching related words, and generating an SQL query statement based on a pre-connected Text-to-SQL module; performing syntax and security checks, executing the SQL query statement to obtain query results; selecting a visualization component to load and display the query results according to the user's query intent, and changing the display method of the query results in response to user actions.

Embodiments of the present disclosure provide a data processing method, relating to the field of data processing. The data processing method comprises: in response to receiving a trigger instruction for executing a data quality monitoring task of to-be-monitored data, executing the data quality monitoring task, and generating M first query statements; extracting a data source of each of the M first query statements; based on the data source, performing merging processing on the M first query statements to obtain a second query statement; and executing the second query statement to obtain an execution result, the execution result being used to determine the data quality of the to-be-monitored data. By merging the first query statements of the same data source to obtain the second query statement, the data quality of the monitoring data can be determined by executing the second query statement once, thereby significantly improving the efficiency of data quality monitoring and bringing a better experience for the user. In addition, the embodiments of the present disclosure provide a medium, an apparatus and a computing device.

The application discloses a kind of based on graph structure's power grid voltage stability margin online prediction method, comprising the following steps: constructing power grid attribute graph model in graph database, and establishing event-driven mechanism to realize the incremental update of topological change;Based on parameterized graph query template, dynamically generate graph database query statement, obtain the node feature matrix and adjacency matrix of prediction time, and convert to sparse tensor format;Constructing spatio-temporal graph convolution network prediction model;Through the incremental update of topological change driven by event-driven mechanism, to drive spatio-temporal graph convolution network prediction model;The prediction result and model intermediate layer node embedding vector are written back to graph database as attribute.This application realizes the millisecond level online prediction of power grid voltage stability margin, meets the real-time, accuracy and adaptability requirements of power system online safety analysis.

Embodiments of the present application disclose a slow query associated data acquisition method, device and equipment and a storage medium. The method comprises: receiving a first operation instruction of a user for a target fingerprint slow query statement in a first display interface, at least one fingerprint slow query statement being displayed in the first display interface; in response to the first operation instruction, obtaining a target execution plan corresponding to the target fingerprint slow query statement by a preset execution plan acquisition function, and performing library table analysis processing on the target fingerprint slow query statement by a preset library table analysis component to obtain a target library table keyword; determining target library table metadata corresponding to the target library table keyword according to a preset correspondence between the library table keyword and the library table metadata; displaying a second display interface, the target library table metadata and the target execution plan being displayed in the second display interface. According to the embodiments of the present application, the associated data of the fingerprint slow query statement can be automatically acquired, and the analysis efficiency of the slow query statement is improved.

The present disclosure provides a method and an apparatus for revising text information, a device, and a medium. A specific implementation of the method includes: acquiring original text information to be processed; generating a query statement based on the original text information, where the query statement is used for searching for a retrieval key point involved in the original text information; searching specified data based on the query statement to obtain reference information related to the retrieval key point; assessing the consistency between the reference information and the retrieval key point; and revising the original text information based on an assessment result.

The application relates to the technical field of artificial intelligence, in particular to a retrieval method and device based on multiple agents, equipment and a medium. Applied to a financial scene, the application realizes the intellectualization and dynamicization of the retrieval process through a multiple-agent cooperative working mechanism. The retrieval core elements are accurately extracted and a dynamic cognitive graph is updated by analyzing the agents, deep semantic mining and correlation expansion are carried out based on the cognitive seeds of semantic agents, the dependence on keywords in traditional retrieval is effectively broken, and the breadth and depth of semantic understanding are improved. The query statement is optimized by combining the extended semantics and the dynamic cognitive graph of the context agent, so that the query is more in line with the real intention and context of the user. The retrieval agent efficiently retrieves the candidate path in the updated dynamic cognitive graph, the recommendation agent filters the optimal result through cognitive consistency scoring, and the accuracy, relevance and logical coherence of the retrieval result are ensured, and the accuracy of the complex information retrieval task is significantly improved.

The application provides a query statement conversion method and device, electronic equipment and a storage medium. The method comprises the following steps: receiving a lucene query statement based on a custom EBNF; the lucene query statement comprises a plurality of sub-query statements and a Boolean operator; parsing the plurality of sub-query statements and the Boolean operator based on a syntax analysis library and the EBNF to obtain an abstract syntax tree (AST); and converting the AST into a real DSL statement according to an ES mapping. In the application, an attribute capable of converting the lucene query statement into the DSL statement is added in the ES mapping, the lucene query statement is parsed into the AST, and then the AST is converted into the DSL statement based on the ES mapping. Since the lucene query statement is relatively concise when being written, the user can easily write the lucene query statement, and after being converted into the DSL statement, the function originally not supported by the standard lucene can be added through the function of the DSL query statement itself.

The application discloses a knowledge base question answering method and system under full-process large language model small sample learning, the method comprises the following steps: question analysis, identifying candidate triples and question types of original user questions through a large language model; query template generation, generating a knowledge base query statement template with placeholders for user questions; knowledge base linking, obtaining matched expressions for the placeholders in the query statement template in combination with a large language model and an entity information index that has been constructed; answer generation, generating a knowledge base query language and returning a final result. Through the small sample learning capability of the large model, the retrieval process is redesigned for the knowledge base question answering task, a model does not need to be trained separately, and the question answering process is simplified; through the powerful knowledge reserve of the large model, the question answering effect and generalization capability are improved.

The application provides a cross-source synchronization table index creation method and device, equipment, storage medium and program product, which can be applied to the technical field of big data. The method comprises the following steps: receiving a query statement for obtaining data from a data warehouse; extracting a query field set and a condition field set from the query statement; obtaining data from the data warehouse according to the query statement, and synchronizing the obtained data to a target table in an online database, wherein the target table comprises data columns corresponding to the query field set; merging the condition field set into a candidate index field set of the target table; calculating a dispersion index of each field in the candidate index field set based on the condition value distribution corresponding to each field in the candidate index field set; selecting a target field set from the candidate index field set based on the dispersion index; and creating an index for each field in the target field set on the target table.

A structured query statement similarity detection method, a device and a medium are provided. The method includes: acquiring first and second structured query statements, and constructing corresponding first and second abstract syntax trees, a correlation degree between the root node in the abstract syntax tree and the query result of the statement being higher than a correlation degree between other nodes and the query result of the statement; traversing a node in the first abstract syntax tree, matching the traversed node with a node at a same level in the second abstract syntax tree, and obtaining a matching result of the node; and determining a statement similarity between the first structured query statement and the second structured query statement based on a matching result of a root node in the first abstract syntax tree, a matching result of a child node of the root node, and their corresponding weights.

The application discloses a data query method and device, electronic equipment and storage medium. The method comprises the following steps: determining a target query statement; determining a target query subject and a target query requirement based on the target query statement; determining a first result set based on the target query requirement; determining a second result set based on the target query subject; and determining a target query result corresponding to the target query statement based on the first result set and the second result set. By adopting the technical scheme, the target query statement is determined, the target query subject and the target query requirement are determined based on the target query statement, the first result set is determined based on the target query requirement, the second result set is determined based on the target query subject, and the target query result corresponding to the target query statement is determined based on the first result set and the second result set, so that the first result set and the second result set are comprehensively determined, the subject relationship and the vector similarity of data are fused, and the accuracy of the retrieval result is improved.

The application belongs to the technical field of databases, and specifically discloses a database query optimization method and system based on metric learning and correlation correction. The method comprises the following steps: constructing a training set based on data in a database table, training a metric learning model based on the training set to learn correlation information between columns, and storing the correlation information as extended statistical metadata; responding to and analyzing a query statement, obtaining single-column statistical information of relevant columns and statistical information of multi-column correlation from the extended statistical metadata; calculating an initial selection rate based on the column independence assumption, correcting the initial selection rate based on the multi-column correlation to obtain a final multi-column selection rate after correction; and estimating query cost based on the final multi-column selection rate, and selecting an execution path according to the estimation result to generate a final execution plan. Through the application, the accuracy of multi-column selection rate estimation can be improved.

This application relates to a data query method, apparatus, device, readable storage medium, and program product. The method includes: in response to a data query request, obtaining data access permissions for the requesting account corresponding to the data query request; the data query request carrying request description data; generating a target query statement corresponding to the data query request based on the request description data and the data access permissions; and querying target data from a database based on the target query statement. This method can improve data query efficiency while ensuring data security.

The embodiment of the present specification provides a data query method and device of a distributed database, wherein the data query method of the distributed database comprises the following steps: obtaining a query statement for querying data in the distributed database; extracting features of query keywords contained in the query statement to obtain query keyword features; determining keyword data distribution corresponding to the query keywords in historical data distribution of the distributed database; generating keyword density features based on the obtained keyword data distribution; inputting the query keyword features and the keyword density features into a base estimation model to estimate data base, and obtaining a base estimation value of target data corresponding to the query keywords as a query result of the query statement.

This invention discloses an AI-based intelligent question-answering method, device, electronic device, and product for games, relating to the field of intelligent question-answering technology. The AI-based intelligent question-answering method for games includes: identifying entity objects in game consultation text through part-of-speech tagging; performing similarity matching between the game consultation text and various question templates in a pre-built question template library to obtain a target question template with the highest matching degree; constructing a graph database query statement based on the question type corresponding to the target question template and the entity objects in the game consultation text; querying data from a pre-built graph database based on game knowledge using the graph database query statement; and generating a response text for the game consultation text based on the query results. The AI-based intelligent question-answering method, device, electronic device, and product disclosed in this invention ensure that the generated response content corresponds to the user's intended question, improving the accuracy of intelligent question-answering for games.

This application provides a method, apparatus, device, medium, and program product for generating training data, which may involve artificial intelligence technology and computer technology. The method includes: inputting a first document from a data source corresponding to a vertical domain text retrieval model into a first large language model to obtain a query statement corresponding to the first document; querying the query statement in the data source to retrieve N second documents; where N is an integer greater than 1; selecting M target second documents from the N second documents that constitute negative samples with the query statement; where M is a positive integer; and for each of the M target second documents, constructing a triplet training data with a partial order relation for a general text retrieval model using the query statement, the first document, and the target second document. This automatic generation method of training data can improve the efficiency and accuracy of training data generation compared to manual methods.

This application relates to the fields of artificial intelligence and data processing technology, specifically providing a data management method, system, device, and medium based on a dual-track verification and self-healing mechanism, aiming to solve the problems of compatibility and logical errors between multiple databases. To this end, the data management method of this application includes: generating first and second target structured query statements based on a user-provided natural language question; verifying the completeness and consistency of the first target structured query statement to obtain a first verification result; verifying the correctness of the execution logic of the second target structured query statement to obtain a second verification result; if the first verification result and / or the second verification result are verification failures, obtaining verification error information, regenerating new first and second target structured query statements based on the verification error information and the natural language question, and continuing verification; otherwise, retrieving target data from the target database based on the second target structured query statement to improve query accuracy.

An information search method, a related apparatus, and a communication system are disclosed. An electronic device may find a related file based on semantics of a query statement, extract, from the related file, information to be searched for by the query statement, and provide the information for a user, so that the user can directly obtain, by performing a search operation, information that the user wants to search for. The electronic device may further provide a function control configured to use the foregoing found information, to help the user quickly use the found information.

This invention discloses a unified data access orchestration and query execution method, a computer device, and a storage medium, belonging to the field of computer technology. The unified data access orchestration and query execution method includes the following steps: S1, determining query parameters; S2, constructing a unified query model; S3, identifying field attribution and modeling query paths; and S4, reasoning and selecting expected paths. This invention achieves a unified structured expression of complex query logic, supports automatic identification of field attribution and path reasoning, and can automatically translate query statements and distribute them to the corresponding databases for execution. It provides an intermediate layer integration mechanism to achieve the final structured return of data. This invention can effectively reduce the complexity of access and management between multiple database systems, improve the flexibility, scalability, and development efficiency of data queries, and is applicable to various scenarios such as data platforms, reporting systems, and data service API platforms.

This application discloses a data query method, apparatus, electronic device, and computer-readable medium, relating to the field of big data processing technology. The method includes: receiving a data query request and obtaining a corresponding time identifier and database identifier; determining the corresponding number of partitions based on the database identifier, and then performing modulo operation based on the time identifier and the number of partitions to obtain a query partition identifier; responding to a change in the time identifier, determining a first historical partition from the historical partitions corresponding to the number of partitions and determining a second historical partition corresponding to the query partition identifier, and copying statistical information corresponding to the first historical partition to the second historical partition; generating a query statement based on the query partition identifier, accessing the second historical partition after copying the statistical information, and then executing the query statement to return query results. This achieves optimal query efficiency while improving the accuracy of data queries.

This invention provides a data query method, apparatus, electronic device, and storage medium. The method includes identifying the query semantics of natural language, matching the query semantics with preset reference data to obtain a target table structure and a query statement, performing query simulation on the query statement to obtain simulation results, and executing the query statement to obtain query results for the target table structure if no query risk is found in the simulation results. If query risk exists in the simulation results and / or the query results do not meet preset query conditions, optimization prompts are generated based on the query semantics and target table structure to optimize semantic priority, enabling a large model to optimize the query statement according to the optimization prompts. Query retries are then performed based on the optimized query statement. Query retries include performing query simulation on the optimized query statement and executing the optimized query statement after no new query risk is found. This invention significantly improves query accuracy, stability, and robustness.

A multi-index join retrieval method includes: querying an auxiliary table based on search conditions to obtain a first auxiliary table result set; transforming the first auxiliary table result set into a first main table result set based on a document association mapping table between the auxiliary and main tables; querying the main table based on search conditions to obtain a second main table result set; comparing the main table documents in the second main table result set with those in the first main table result set to obtain a third main table result set; searching the document association mapping table and the first auxiliary table result set based on the third main table result set to obtain a second auxiliary table result set; and concatenating the documents in the third main table result set and the second auxiliary table result set to obtain a query result set that satisfies the query statement. During retrieval, a pre-built JoinDocMap between each auxiliary table and the main table is used to obtain relevant document information, avoiding the performance inefficiencies caused by multiple rounds of subqueries in join query execution, thus significantly improving the execution efficiency of multi-index join retrieval.