67 results about "Conjunctive query" patented technology

The invention discloses a complex SQL query dynamic rewriting method based on AST and a server, and relates to the field of data rewrite.The method comprises the steps that in response to a received target database type, an original SQL query statement is analyzed into AST; an SQL processor is initialized; recursively traversing a selection statement structure of the main query, and recursively traversing a sub-query structure nested in the selection statement structure; recursively traversing each selected statement structure in the joint query; recursively traversing conditional expressions in the updated statements, the deleted statements and the inserted statements or nesting and selecting statement structures; converting the rewritten AST into an SQL (Structured Query Language) query statement after dynamic rewriting; and returning the dynamically rewritten SQL query statement, and rewriting the SQL expression and the SQL statement structure in the AST according to a preset dynamic modification logic. The technical problem that a complex nested structure cannot be processed in a traditional SQL enhancement or modification mode can be effectively solved.

The invention is suitable for the technical field of data query, and provides an index query method and device, electronic equipment and a storage medium, and the index query method comprises the following steps: obtaining a first type of query language statement input by a user; performing grammar analysis on the first type of query language statement based on a predefined grammar rule to generate a corresponding analysis tree; traversing the analytic tree, identifying a query target in the first type of query language statement, and constructing a query semantic object based on the query target, the query target including one or more of an index and a physical table; and according to the query semantic object, generating a second type of query language statement corresponding to the first type of query language statement for an underlying data system to perform index query. According to the scheme, by introducing the query semantic object and supporting mixed recognition and processing of the index and the physical table, the problems that in an existing query mode, flexibility is insufficient, dynamic parameters cannot be expressed, and multi-source joint query cannot be supported are solved.

The invention provides a multi-object tracking method based on global-local feature joint modeling, and the method comprises the steps: carrying out the multi-scale image pyramid generation of a current frame of a large-scene high-resolution video, and obtaining a plurality of multi-scale image representations with different resolutions; target detection is carried out in a sliding window mode, a non-maximum suppression algorithm is used for fusing detection results under all scales to construct a joint query group containing global target query and local target query, the joint query group is input into a decoder and is associated with encoded image features through a cross attention mechanism, and a target query result is obtained. Outputting global-local joint feature representation; and in combination with a shielding state prediction result of the target, performing optimal matching on the current detection target and the trajectory set by adopting a shielding state perception matching strategy, and dynamically updating or discarding the trajectory. According to the method, the tracking precision and continuity of multiple objects in a large-scene high-resolution video in a dense shielding environment can be effectively improved, and collaborative optimization of global and local features is realized.

The invention provides a multi-modal data joint query analysis method and system supporting natural language interaction, and relates to the technical field of data query analysis. Historical operation data, audio data and text data of a user on an intelligent search platform supporting natural language interaction are collected; modeling the historical operation data to obtain a user preference vector, performing voice recognition and text standardization processing on the audio data to obtain standard query data, and integrating the standard query data and the text data into context information; an attention mechanism-based algorithm is used for semantic understanding and intention recognition to obtain an intention feature vector, and the intention feature vector is fused with a user preference vector to obtain a classification result; and finally, based on the result, querying in a preset multi-modal database through a collaborative filtering algorithm to obtain a joint query result, so that personalized accurate query of the multi-modal data under natural language interaction can be realized, and the result fits the intention and long-term preference of the user.

The invention provides a multi-data-source joint query method, device and equipment based on a large language model, and the method comprises the steps: in response to a natural language query request, extracting database table structure information of a target data source from a metadata knowledge base; inputting the natural language query request and the database table structure information into a large language model, and outputting a cross-database execution plan; disassembling the cross-library execution plan into an independent query subset which is executed concurrently and a sequential query subset which has a dependency relationship; concurrently executing multi-database dialect SQL (Structured Query Language) generation and query operation on the independent query subset to obtain a first query result; performing pre-query on the sequential query subset according to a dependency relationship sequence, and injecting a query result into a subsequent query to obtain a second query result; and fusing the first query result and the second query result and outputting a standardized query result. According to the method, the technical threshold is reduced, cross-library joint query is realized, error accumulation in an intermediate link is avoided, and the query accuracy is remarkably improved.

Various embodiments of the present disclosure provide federated query processing techniques for monitoring data access patterns through federated queries and intelligently caching disparate data segments based on the data access patterns. The techniques include determining a relative priority for a data segment of a third-party data source based on a plurality of federated queries. Each of the plurality of federated queries may reference data segments from a plurality of disparate data sources. The relative priority may be indicative of a priority of the data segment relative to other data segments. In response to a determination that the relative priority satisfies a priority threshold, the techniques include storing a data segment in an intermediary local data source and initiating the performance of a data segment redirect configured to redirect a subsequent federated query associated with the data segment to the intermediary local data source.

The invention provides an industry knowledge base dynamic construction method and system based on multi-source heterogeneous data, and relates to the technical field of data processing.The method comprises the steps that target industry multi-source heterogeneous data, user historical behavior data, a natural language question text and a processing text are collected to generate a query data stream; mapping the user question into a query semantic vector, converting the user interaction behavior into a behavior feature vector, and generating a joint query vector; industry knowledge units are automatically extracted from multi-source heterogeneous data and external knowledge sources, and a dynamic knowledge topological graph is constructed; establishing a dynamic knowledge routing table, taking the joint query vector as a routing request, matching a target knowledge node, recording a query path and caching an association rule; and counting and querying path node transition probability to identify a hotspot path, mining a deep association rule, and reversely adjusting a knowledge topological graph structure, so that user intentions can be accurately matched, an industry knowledge base can be dynamically optimized, and knowledge retrieval and association efficiency can be improved.

The invention relates to the technical field of artificial intelligence and intelligent manufacturing, and discloses a multi-source heterogeneous data and large language driven process intelligent design system and method, and the system comprises a multi-modal data processing module which is used for achieving the structural information extraction of multi-source heterogeneous engineering data; the multi-source heterogeneous mixed database construction module is used for realizing storage of multi-source process knowledge and joint query of a database; the large model construction and optimization module is used for constructing a large model to realize user intention understanding, process knowledge fusion and process scheme generation and optimization; the intelligent processing technology collaborative design system provides a multi-mode interaction interface for a user to realize full-process automatic technology design from demand input to scheme output; according to the system and the method, the full-process intelligence from part information extraction, process knowledge retrieval, process scheme generation to simulation verification optimization is realized, and the system and the method can be widely applied to machining process design and optimization scenes in the fields of industrial mother machines, robots, high-end equipment manufacturing and the like.

Implementations relate to obtaining, from each agent of a plurality of agents, a respective agent query, wherein each respective agent query includes a respective natural language request for performance of a respective generative task; aggregating each respective agent query to form a joint query; causing the joint query to be processed using a generative model to generate responsive content; and broadcasting, to each agent of the plurality of agents, at least some of the responsive content generated using the generative model, wherein the responsive content is responsive to the joint query.

The invention discloses a hospital examination and inspection result sharing method based on big data, and relates to the technical field of hospital examination and inspection result sharing. Examination data and inspection data are respectively stored in independent databases, and the two types of data are intelligently linked by using a unique identity label of a patient and a time stamp; the format, the time sequence and the semantic information are accurately matched to form a continuous and visual comprehensive disease course record; introducing a deep learning model, carrying out natural language processing on an unstructured text in the inspection data, and automatically converting an image description and a diagnosis report into structured data and a predefined semantic tag; according to the method, the workload of manual structuring is reduced, distributed storage, dynamic updating and multi-dimensional index query modules are constructed based on a big data analysis platform, real-time retrieval and joint query are conducted on comprehensive disease course data records, meanwhile, an early warning report is generated through an anomaly detection algorithm, and a basis is provided for clinical decision making.

The application discloses a data query method and device, electronic equipment and computer readable medium, relates to the technical field of computers, and a specific embodiment includes: receiving a data query request, obtaining a corresponding instruction type identifier and data timeliness identifier; positioning a target database table according to the instruction type identifier and the data timeliness identifier, and then determining the number of the target database table; in response to the number being multiple, obtaining query mode information corresponding to the instruction type identifier, determining a query statement assembly order based on the query mode information, assembling the query statement and the target database table based on the query statement assembly order, and generating a joint query statement; executing the joint query statement, and then outputting data obtained by querying. Thus, when data is queried, the range of the query is narrowed, and the data query is more accurate and faster.

The application belongs to the field of connection cardinality estimation, and provides a method and system for adaptive multi-table connection cardinality estimation. The method for adaptive multi-table connection cardinality estimation comprises receiving an input query statement and analyzing the contained relationship and the connection relationship of multi-table connection of the query statement; the analysis result of the query statement is subjected to feature vectorization, and then the cardinality of the query statement is predicted based on a cardinality estimation model; the query statement is converted into a database query prompt, a query optimizer is operated through the prompt, the query statement is executed, and a real cardinality value is obtained; the feature vector corresponding to the analysis result of the query statement and the real cardinality value constitute a training sample, and the cardinality estimation model is retrained to learn the correlation of multi-table joint query, which is used for estimation of the next connection cardinality.

Several examples of the disclosure relate generally to federated queries for accessing data from multiple data silos associated with a product, such as a medical imaging device. Several examples of the disclosure relate specifically to a language model for generating such federated queries. Several examples of the disclosure relate specifically to fine-tuning such a language model.

Embodiments of the present specification provide a data query method, system and device, wherein the data query method comprises: receiving a data query request; performing structural analysis on at least one joint query statement to determine a plurality of leaf query statements; from the plurality of leaf query statements, screening a target leaf query statement and a target query result set of the target leaf query statement that meet a preset screening condition; determining whether each target query result in the target query result set hits a to-be-queried leaf query statement to obtain a determination result; and determining a target query result corresponding to the data query request according to a go-or-leave determination rule corresponding to the to-be-queried leaf query statement and the determination result. By using the target query result set to check whether the to-be-queried leaf query statement is hit, the target query result is obtained, and there is no need to calculate intermediate sub-joint query statements, thereby controlling the invalid performance and memory loss of a large number of query intermediate sub-joint query statements, and improving the efficiency of data query.

The invention provides a mixed retrieval knowledge base construction system and method based on a keyword library and vectors. The system comprises a facade module, a timing module, a knowledge base creation module, a knowledge query module, a keyword module and a vector module. The method comprises the following sub-steps: S1, creating a knowledge base and segmenting an uploaded knowledge document into text blocks; s2, creating a keyword library, and storing the obtained keywords in the keyword library; s3, performing keyword updating on the knowledge document by using the content in the keyword library; s4, performing mixed knowledge query of keywords and vectors; according to the method, the need for data uploading is reduced through keyword localization and vector calculation, so that the risk of data leakage is effectively reduced, and the applicability of the system in commercial products is enhanced; by combining two technologies of keyword retrieval and vector retrieval and through keyword and vector joint query, the accuracy and recall rate of knowledge retrieval are effectively improved.

The invention discloses a spatial semantic enhanced real estate registration knowledge retrieval enhancement generation method, and belongs to the cross technical field of geographic information technology, natural language processing and retrieval enhancement generation. Extracting spatial geometry and topology constraint features, ownership business features and text semantic features, and generating a joint query representation in a unified vector space; and performing multi-level mixed retrieval in the real estate registration multi-mode knowledge base, fusing retrieval results to construct context enhanced representation, inputting the context enhanced representation into the large language model, generating a structured response, and completing output. According to the retrieval reasoning technology based on spatial semantic enhancement, an efficient, accurate and reliable intelligent processing scheme is provided for real estate registration service query, the service query quality and efficiency are remarkably improved, and good application and popularization value is achieved.

The invention provides a method, a device, equipment and a medium for constructing a photovoltaic power station design rule base based on a dynamic multi-dimensional tree, and the method comprises the steps: determining dimensions according to the design requirements of a photovoltaic power station, constructing an independent sub-tree based on the dimensions, and designing a dynamic multi-dimensional tree data structure through the dynamic association of cross nodes; inputting the core content and the extension information of each rule into a corresponding database table; when a new rule is updated, analyzing the new rule based on a natural language processing technology, extracting the content of the new rule and the change range of the new rule, and updating the rule base; based on a multi-dimension joint query function, corresponding rules are queried according to function classification and risk level dimensions, so that the problem that design rules of a photovoltaic power station are difficult to manage and query due to the fact that the rules are various in type and complex in content and have multi-dimension classification requirements is solved.

This application discloses a data query method, apparatus, storage medium, and electronic device, relating to the field of big data technology. The method includes: receiving a query task sent by a target object, wherein the query task is a task to query first data in M ​​databases; dividing the query task into N query subtasks through a scheduler, and sending each query subtask to each task executor; executing each query subtask through each task executor, and extracting N second data from the M databases based on M data connectors; and determining the first data based on the N second data. This application solves the problem in related technologies where data from different databases needs to be extracted to a data warehouse using ETL technology, and then a final joint query is performed in the data warehouse, resulting in poor performance of joint queries based on different databases.

The application provides a resource query method and device, electronic equipment and storage medium; the method comprises the following steps: acquiring a query statement, wherein the query statement is used for querying at least one type of resource on a container orchestration platform; a syntax tree structure corresponding to the query statement is constructed, wherein a node in the syntax tree structure is used for representing a clause corresponding to the query statement; the syntax tree structure is converted into at least one application programming interface request; resource data associated with the at least one type of resource is acquired based on the at least one application programming interface request; and aggregation is performed on the resource data to obtain a query result corresponding to the query statement. Through the application, a unified query interface can be provided to access different types of data sources, thereby realizing joint query across resource types, reducing the complexity of resource query, and reducing the use threshold without the need to learn multiple tools.

The present application belongs to the field of human interaction relationship detection, and discloses a human interaction detection method based on dynamic noise reduction distillation and prior purification, wherein a global encoding feature is generated for an image sample through an encoder; a learnable query, a real query and a noise query are constructed, the real query and the noise query are added to obtain a joint query, and the learnable query and the joint query are spliced to generate a mixed query; the global encoding feature and the mixed query are input into a decoder, the output of the decoder is extracted to obtain a student prediction set and a teacher prediction set, and a total loss is calculated for optimization update. The method effectively balances the noise reduction strategy and the knowledge distillation, minimizes the influence of negative samples in query distillation, and retains positive samples at the same time.

The present invention relates to a method and apparatus for high-performance analysis of delimiter format files. The method includes: sampling control characters in an input file in an iterative manner to determine the symbol state and logical position of the control characters; determining the character conversion level to be selected in a finite state transducer model according to the control characters, where the character conversion levels include a record level and a field level; splitting the input file into text blocks of equal size and placing them in idle processing units, implementing parallel scanning based on the finite state transducer model, and using SIMD to accelerate the recognition of delimiters to generate a bitmap index; performing queries based on the bitmap index, including a keyword search query mode and a file union query mode. The present invention realizes parallel processing at the thread level and instruction level, solves the speed bottleneck problem that the processing of CSV files is limited by the inherent format and can only be serially processed, and improves the processing speed.

The present application belongs to the technical field of data retrieval, and particularly relates to a method for improving data retrieval speed, comprising the following steps: S1, generating a multi-table fuzzy query request; S2, building a business physical view service; S3, dimension reduction of the multi-table fuzzy query request, and single-table query of the business physical view; wherein the business physical view is classified into a single physical view for the same type of business function. The present application establishes a business physical view service, creates and updates the business physical view to be queried in real time, and performs full-text indexing on the business physical view, so as to provide single-physical-view fast fuzzy query for business query, make the fuzzy query not limited by left and right fuzzy queries, and greatly improve the query efficiency from tens of seconds or even hundreds of seconds to tens of milliseconds, thereby greatly improving the user experience, especially for multi-table joint query and multi-field simultaneous query, which more embodies the query advantage.

The invention discloses a joint query method and system for multi-source heterogeneous distributed spatio-temporal data nodes, and belongs to the field of data management and query analysis of geoscience spatio-temporal data. The method comprises the following steps: firstly, carrying out metadata standardization cataloguing and registration on an earth science spatio-temporal data set, and meanwhile, constructing a global unified time axis index to realize mapping and matching of different time systems; analyzing a client query request, generating a logic execution plan through expanded space-time function verification, and introducing a custom rule to a volcano optimizer to generate a physical execution plan with the minimum cost; and finally, converting the physical operator into a code capable of being executed in a distributed manner by adopting a dynamic code generation technology, efficiently executing the code through a spatial distributed computing framework, and returning a result. According to the method, the problems of difficulty in space-time alignment and low query efficiency of multi-source data in the field of earth science are solved, and a high-performance and extensible solution is provided for complex space-time analysis.

The invention relates to the technical field of application software patch management, and provides an application software patch dynamic dependency management method and system and computer equipment. The method comprises the following steps: based on an uploaded patch file, combining a patch content file type, extracting a patch content feature set, and carrying out encryption processing to generate a content fingerprint; querying a branch-content fingerprint database by taking the content fingerprint and the code branch identifier corresponding to the patch file as a joint query primary key; if the matching record exists, adding the unique identifier of the matched patch to the dependency path of the current patch, and constructing a dependency chain; if the matching record does not exist, writing the content fingerprint of the patch file and the newly generated code branch identifier into a branch-content fingerprint database; wherein the branch-content fingerprint database is constructed based on the content fingerprint and the code branch identifier corresponding to the patch file.

A client device receives one or more inputs for generating a data visualization from a data source. A device determines one or more requirements for generating a data visualization. A device sends a request to a network gateway communicatively connected to a client device and a plurality of data servers, and receives capabilities of each data server from the network gateway. The device determines, from the received capabilities, that a first data server of the plurality of data servers includes a first set of capabilities that meet requirements for generating the data visualization. A device sends one or more queries to a first data server via a network gateway and receives one or more data sets from a data source from the first data server. The device generates a data visualization according to the acquired data set and displays the data visualization.

The application discloses a data synchronization method and device and electronic equipment. The method is applied to a first electronic device and includes: obtaining configuration information, the configuration information including mapping information, filtering conditions, connection relationships of P target data tables, and storage of the P target data tables in a target database, the mapping information including a mapping relationship between a plurality of fields in an index of a search engine and a plurality of to-be-queried fields corresponding to the P target data tables, the filtering conditions being used for screening field values of the to-be-queried fields corresponding to at least one target data table satisfying a preset condition, and P being an integer greater than 1; generating a query statement according to the configuration information; performing joint query on the P target data tables in the target database according to the query statement to obtain target data; and synchronizing the target data to the index. Based on the technical scheme of the application, the data synchronization efficiency between the search engine and the database can be improved.

This application provides a method and system for joint query analysis of multimodal data supporting natural language interaction, relating to the technical field of data query analysis. This application collects historical operation data, audio data, and text data from an intelligent search platform supporting natural language interaction; then models the historical operation data to obtain a user preference vector; processes the audio data through speech recognition and text standardization to obtain standard query data, and integrates it with the text data to form contextual information; then uses an attention-based algorithm for semantic understanding and intent recognition to obtain an intent feature vector, and fuses it with the user preference vector to obtain a classification result; finally, based on this result, a collaborative filtering algorithm is used to query a pre-set multimodal database to obtain joint query results. This enables personalized and accurate querying of multimodal data under natural language interaction, ensuring that the results match user intent and long-term preferences.

The present invention discloses an automatic address cleaning method based on a geographic information system weight analysis model. The method segments and compares large elements in address information based on a standard coordinate system, and constructs a weight analysis model based on the results of a one-way query of the subject's name and address and a joint query of large elements. The weight value can be dynamically improved to judge the accuracy of the address information, perform corrections to obtain accurate address information, and improve the accuracy of address information matching.

The present application relates to the field of computer processing technologies, and provides a method, a device, a computer device, and a readable storage medium for generating a business engine instance. The method includes: obtaining expression information of a target service in a set format; determining a target structured query language according to first-class data in the expression information, where the source of the first-class data is a data set obtained by a multi-table joint query; obtaining a rule template according to information other than the first-class data in the expression information and a preset rule library; and obtaining an engine instance according to the rule template and the target structured query language. By using this method, the multi-table joint query ability can be improved, and the construction of a complex engine instance with attached logical judgment can be completed.

The present invention relates to the field of data query technology, and in particular to a data query method, device, electronic device, and storage medium. The method comprises: obtaining data to be queried, wherein the data to be queried includes structured conditions and vectors to be queried; customizing a joint query scanning path in a database management system; calculating the total cost of the joint query of the structured conditions and the vectors to be queried based on a cost model, selecting the path with the minimum total cost from the customized joint query scanning path as the target joint query scanning path and converting it into a target joint query scanning task, performing a joint query in the database management system based on the target joint query scanning task, and obtaining target query data corresponding to the data to be queried. The present application calculates the path with the minimum total cost as the target joint query scanning path through a cost model, and searches the target joint query scanning path in combination with the structured conditions to narrow the search range of the vector index, which is conducive to improving the query speed.