73 results about "Relational query" patented technology

The invention relates to a government affair file information extraction and question answering method and device and a medium, and the method comprises the steps: carrying out the entity extraction of a government affair file through employing a BERT-CRF joint model, and obtaining a structured entity set; performing relation extraction on the structured entity set to generate a semantic relation set between the entities; constructing a knowledge graph according to the structured entity set and the semantic relationship set, storing entity nodes into a graph database, and storing an embedded vector of an entity text into a vector database; when a query request of a user is received, relation query of the graph database and semantic retrieval of the vector database are carried out, sub-graph structures and semantic matching vectors related to query are extracted, and a mixed retrieval result is obtained; and inputting the mixed retrieval result into a large language model, and generating a question and answer response text conforming to a preset format by applying a dynamic prompt template. According to the method, the document processing efficiency and accuracy are effectively improved, and a solid technical support is provided for intelligent management of government affair documents.

An illustrative method for querying multiple datasets may include generating, based on models each associated with and defining attributes of a different datasets stored in a plurality of data stores, a semantic layer defining relationships between the models and that provides a centralized application programming interface (API) for exposing the datasets by way of a common query language, receiving, by way of the centralized API, a query request for information that depends on data included in multiple datasets included in the plurality of datasets, querying, based on the query request and the relationships between the models defined by the semantic layer, the multiple datasets, and presenting, based on the querying, a query result representative of the information that depends on the data included in the multiple datasets.

The invention discloses a data warehouse multi-hop relationship quick retrieval method and system based on a graph embedded index, and relates to the technical field of multi-hop relationship retrieval data processing. The quick retrieval method for the multi-hop relationship of the data warehouse based on the graph embedded index comprises the following steps of: monitoring data flow interference; monitoring index updating timeliness; monitoring the query accuracy of the multi-hop relationship; and timely monitoring of data query response. According to the method, whether to perform graph model modeling to obtain the graph model is determined by judging whether to trigger the interference suppression mechanism, then the multi-level index is constructed based on the graph model, and whether to trigger the index step length updating mechanism is determined based on the index updating timeliness judgment result; and finally, based on a multi-hop relationship result query accuracy verification result, determining whether to trigger a candidate node screening range shrinkage mechanism, thereby achieving the effect of improving the multi-hop relationship retrieval efficiency of the data warehouse, and solving the problem of low multi-hop relationship retrieval efficiency of the data warehouse caused by data flow interference in the prior art.

The invention discloses a data tracing method and device based on a runtime snapshot. Comprising the steps of generating a runtime memory snapshot file based on report traceability information; analyzing the runtime memory snapshot file, extracting all keys in the first mapping relation to construct a header character set, and querying N metadata identifiers corresponding to N header characters according to the first mapping relation; accessing a report data result storage area based on the N metadata identifiers to obtain a data value list, and rendering to generate a visual report snapshot; for each metadata identifier, extracting the metadata identifier of each metadata which directly depends on and indirectly depends on the metadata identifier from the task detail information associated with the metadata identifier, and obtaining a single metadata tree based on the hierarchical dependency relationship among the metadata; rendering and generating N metadata tree snapshots based on the N metadata trees; and displaying the metadata circulation process corresponding to the abnormal data value by skipping to display the metadata tree snapshot of the metadata identifier corresponding to the report data column where the abnormal data value is located.

The invention relates to the technical field of distributed storage, can be applied to business scenes of financial science and technology, medical health and the like, and discloses a data storage method, device, equipment and medium based on partition identifier mapping, and the method comprises the following steps: receiving a file and dividing the file into data blocks to generate block identifiers; generating a partition identifier based on the file identifier and the block identifier through hash mapping; creating a partition disk pack mapping table and writing an initial relationship; querying the mapping table to obtain a disk group, and writing the data block into a physical disk to generate a copy; monitoring the health of the disk, keeping the partition identifier and the block identifier unchanged when a fault occurs, and updating the mapping relation to a new disk group; and receiving a read-write request of the target partition identifier, querying the mapping table to obtain the target disk pack, and executing access. According to the method, the partition identification and the block identification are kept unchanged, fast fault tolerance is achieved only by updating the mapping relation, metadata updating expenditure is reduced, bottom layer change is shielded through partition identification routing, and access transparency and high availability are achieved.

The invention discloses a three-dimensional semantic knowledge graph construction method for geographic entity space-time relationship, and relates to the technical field of knowledge graph construction, comprising: acquiring a unified reference geographic entity stream, selecting a mutually covered geographic entity pair set based on XY axis projection overlapping detection, and reading a sensor precision file; determining an up-and-down orientation relation based on a bounding box vertical extreme value; querying a preset layer thickness mapping table to determine a coarse-grained sectioning layer thickness, calculating coarse-grained vertical coverage in the Z-axis direction, defining a crossing depth interval as a coarse-grained vertical index, and comparing the coarse-grained vertical index with a first threshold library to generate a preliminary up-down relationship state tag; and for the ambiguous or envelope state entity pair, determining a local depth range based on a coarse-grained vertical index, performing heavy new sampling by using a fixed fine-grained sectioning layer, generating a second threshold library for rejudgment by revising a threshold, and forming a revised map version. The vertical semantic ambiguity can be eliminated, and the accuracy of judging the upper and lower relationships of the geographic entities is improved.

A causal inference stack implements a targeted maximum likelihood scheme to conduct causal analysis of the observational data. At a data-handling layer, the causal inference stack obtains one or more memory locations for a dataset and establishes analysis nodes to setup localized data handling for the memory locations. At a data classification layer, the causal inference stack characterizes the missingness of the dataset. At a pipeline layer, the causal inference stack obtains a data element dependency query from a user and sets up an end-to-end solution path to determine the presence of a causal relationship between data elements identified in the data element dependency query.

The invention relates to the technical field of data processing systems, and discloses a graph neural network driven complex relation data processing system, which comprises a first graph data processing subsystem, a second graph data processing subsystem and a graph relation management central system, the first graph data processing subsystem comprises a first AI processing module, a first AI big data module, a graph structure construction unit, a graph embedding generation module and an authentication reasoning unit. According to the scheme, the multi-source data is converted into the dynamic attribute graph containing the time dimension through the graph structure construction unit, multi-dimensional modeling of the node attributes and the edge relation is supported, and the limitation that a traditional system only stores the static corresponding relation is solved; according to the method, the graph neural network is utilized to generate the node embedding vector containing the neighborhood relation, multi-hop relation query and community detection are combined, high-order complex relation reasoning such as user-transaction-equipment three-level association path analysis and abnormal sub-graph recognition is achieved, and the deep analysis requirements of scenes such as financial risk control and supply chain traceability are met.

The invention relates to the technical field of precision machining control, and discloses an intelligent control method for a cutting path of a scribing machine, which comprises the following steps: acquiring a load current signal of a main shaft servo motor in real time and storing the load current signal into a sliding window data queue; performing weighted differential calculation to obtain a real-time load change rate representing a load trend, and calculating an average absolute deviation to obtain an oscillation state quantity representing load dispersion; querying based on a preset nonlinear gain scheduling relationship to obtain a first speed regulation coefficient and an oscillation suppression coefficient; according to the method, an orthogonal dual-channel feed-forward control mechanism is constructed in the same data window, and multiplication cooperation of weighted differential and dispersion statistics is utilized, so that a feed speed set value is corrected in real time; the problems of phase lag and response mismatch of conventional feedback control in the case of transient impact and microcosmic oscillation of hard and brittle materials are solved.

The invention relates to the technical field of image processing, can be applied to business scenes of financial science and technology, medical health and the like, and discloses an image retrieval method, device and equipment based on feature fusion and a medium, and the method comprises the following steps: receiving a to-be-processed image, and extracting basic features through a convolutional neural network; respectively processing the basic features through a global feature branch module and a local feature branch module, and generating an image overall representation vector and an image region detail vector; fusing the two feature vectors to generate a fused feature vector; and generating an image retrieval identifier based on the fused feature vector, establishing a corresponding relationship between the image retrieval identifier and the to-be-processed image, and when a retrieval request is received, querying the corresponding image based on querying the image retrieval identifier and the corresponding relationship. According to the method, the image features are efficiently extracted through the single-stage network architecture, the unique index is generated, high calculation overhead and low efficiency of a traditional double-stage feature extraction method are avoided, and the image retrieval speed and accuracy are improved.

The invention discloses an unstructured data connection query optimization system and method based on a twin network, and belongs to the field of unstructured data processing. Comprising a feature extraction module for extracting feature vectors of different types of unstructured data by using a deep learning model; the twin network module is used for converting the feature vector into a low-dimensional embedding space; the judgment layer module is used for outputting a connection matching probability through a full-connection network after the feature difference and the original features are spliced; the threshold decision module is used for determining an optimal upper and lower threshold pair through adaptive mapping and grid search and dividing a connection matching probability into an automatic decision area and a recheck area, and the recheck area is used for further judging a connection relationship through a special reasoning model; and the query optimization module is used for optimizing a query execution plan of the unstructured data based on the connection matching result. According to the method, efficient unstructured database connection operation can be realized, an automatic decision-making and accurate rechecking mechanism is supported, and the accuracy and efficiency of database query connection operation are remarkably improved.

The invention provides an audit text classification filing method and system suitable for audit large model training, and relates to the technical field, the method comprises the following steps: carrying out entity identification and relation extraction on an unstructured audit document to generate a knowledge graph, and extracting a sub-graph structure as a feature representation; performing node embedding learning by using a graph neural network, generating a document vector containing structure and semantic information, and determining a document attribution category through an attention mechanism; and a natural language retrieval request can be analyzed, multi-hop path reasoning is executed, and a document corresponding to an implicitly associated extension node is obtained. The audit document classification accuracy is improved, efficient association query is realized, and the audit knowledge mining capability is enhanced.

The application discloses an ontology relationship progressive disclosure method and system for agent interaction, and the method comprises the following steps: obtaining an ontology relationship query request initiated by an agent; determining an ontology relationship disclosure authorization level based on a user identity, an agent role, a query intention and a historical inquiry path; generating a candidate ontology relationship path according to a target entity in a data ontology graph; performing reservation, hiding, desensitization or aggregation processing on entities, relationships and attributes in the candidate path based on the authorization level, a relationship sensitive label, an attribute sensitive label and a path hop limit to obtain a disclosable ontology segment; outputting entity, relationship, attribute and source information of different granularities in a layered manner according to a progressive disclosure state machine; reviewing the risk of unauthorized disclosure, sensitive combination, path accumulation and reasoning leakage of the to-be-output segment; and outputting the segment to the agent and generating an audit record after the review. According to the application, the risk of unauthorized disclosure and reasoning leakage of the agent when calling enterprise data ontology can be reduced.

The invention discloses a flow gateway vertical calling method and device, and relates to the technical field of computers. A specific embodiment of the method comprises the following steps: in response to a received call request sent by a client, analyzing target domain name information from the call request; determining a target machine room where the gateway is located, obtaining a first mapping relationship between a virtual address corresponding to the target machine room and the domain name information, and querying a target virtual address corresponding to the target domain name information according to the first mapping relationship; and querying one or more target service instances corresponding to the target virtual address according to a second mapping relationship between the virtual address corresponding to the target machine room and the one or more service instances, thereby sending the calling request to any one of the one or more target service instances. According to the embodiment, the vertical calling of the gateway is realized by configuring the virtual address of the machine room, the network delay and the cross-machine-room communication cost are reduced, the flow processing efficiency is improved, and the system stability is improved.

The present invention provides a relationship update method, a relationship query method, an apparatus, a device, and a medium, and relates to the field of data management technology. In the method, an association relationship to be added is obtained; the association relationship includes an associating object, an associated object, and the relationship attributes between the associating object and the associated object; from the association relationships used for relationship query, an association relationship with the same object as the association relationship to be added is determined as a target matching association relationship; using the object in the association relationship to be added, the object in the target matching association relationship is replaced to obtain a first replaced association relationship; for the first replaced association relationship, the relationship attributes in the association relationship used by the first replaced association relationship are used to update the relationship attributes in the first replaced association relationship to obtain a first newly added association relationship; the newly added association relationship and the association relationship to be added are stored to update the association relationship. The present invention can improve data query efficiency.

The present invention discloses a blockchain-based carbon trading data processing method and system. The present invention relates to the field of carbon trading technology, including accepting data from different tenants and customers, and then a unified customer authority management center to ensure data security, allocating different customer data to different ledgers, and the system maintaining a correspondence between system organizations and blockchain organizations in a configured manner, querying the blockchain organization and ledger information to which it belongs, so as to determine the final information submitted to the chain. The blockchain-based carbon trading data processing method and system, through the proposed construction of a blockchain-based carbon emission verification Internet platform, uses blockchain technology to directly collect data in real time, automatically generates reports on the platform, and the report results can be directly connected to the supervision and trading system. Supervision, trading, and financial institutions can all penetrate and view the original data, thereby ensuring that the carbon emission verification process is transparent, standardized, and efficient.

Embodiments of the present disclosure relate to a traffic detection method, device, equipment and medium, wherein the method comprises: in response to a call request for a preset traffic statistics function in a kernel space, obtaining a first process identifier and corresponding current consumed traffic of the traffic statistics function; calling a query interface of a preset network packet filtering eBPF module, and querying whether the first process identifier is contained according to a preset correspondence relationship in a preset virtual file system; if the first process identifier is contained, querying and obtaining the historical total consumed traffic corresponding to the first process identifier in the correspondence relationship through the query interface; calculating the sum of the historical total consumed traffic and the current consumed traffic to obtain the current total consumed traffic, and calling a write interface of the eBPF module to write the historical total consumed traffic of the correspondence relationship as the current total consumed traffic. In the embodiments of the present disclosure, the current total consumed traffic can be counted with process as granularity, thereby the accuracy of traffic statistics can be improved.

The present invention relates to the field of artificial intelligence technology, and provides an artificial intelligence-based data query method, device, electronic device, and medium. The method comprises: scanning database statements in a target database log to obtain database join query statements; analyzing the database join query statements based on table structure information of a target project to obtain a main table and sub-tables, as well as the corresponding relationship between the main table and the sub-tables; creating a first entity relationship diagram based on configuration information of the target project and the corresponding relationship between the main table and the sub-tables; verifying the first entity relationship diagram to obtain a second entity relationship diagram; and performing a table relationship query in the second entity relationship diagram according to a table relationship query condition to obtain a query result. The present invention creates the first entity relationship diagram based on the configuration information of the target project and the corresponding relationship between the main table and the sub-tables, thereby improving the efficiency and accuracy of data table relationship queries.

The present invention discloses a heterogeneous data fusion indexing method and system based on knowledge graph, comprising the following steps: analyzing entity types and relationship types in heterogeneous graphs, synchronizing and defining entity type data respectively, and defining heterogeneous entity mapping relationships; using graph adaptation to obtain entity and relationship data from two types of heterogeneous graphs respectively, and caching the data such as message middleware; constructing a view domain knowledge graph and a business domain knowledge graph; fusing the constructed view domain knowledge graph and business domain knowledge graph to construct a fusion index subgraph; performing mapping relationship analysis and mining based on the constructed fusion index subgraph to achieve disambiguation and fusion of entities in the original graph; providing a standard and unified relationship query interface for heterogeneous graphs and fusion index subgraphs; this solution constructs a data fusion index subgraph through entity mapping of the two types of knowledge graphs to achieve fusion of heterogeneous data.

This invention provides an efficient and verifiable query method for blockchain that supports rich retrieval, relating to the field of blockchain technology. This invention performs relational modeling on data in the blockchain to achieve rich queries; after relational modeling, different data types in the blockchain are stored in different data storage modules; indexes are built for the data in blocks to support efficient verifiable relational queries and verifiable key-value queries. Block data and historical data are indexed using aggregated MB trees, while state data is indexed using sorted balanced binary trees. This invention supports rich query types, allowing retrieval of different attributes to meet the needs of user data analysis and data mining; the queries are verifiable, ensuring correctness and completeness, achieving trusted traceability of the blockchain, improving the efficiency of verifiable queries, expanding the application scenarios of blockchain in production and daily life, and meeting more application needs.

The invention provides a data security management and control method, system and device based on a data label and a medium, and relates to the technical field of data security, the method comprises the following steps: capturing an access request for target data, and analyzing access subject information and an access object identifier used for positioning the target data from the access request; according to the access object identifier, querying a mapping relationship stored in a pre-constructed independent label knowledge base, and obtaining a structured data label corresponding to the target data; generating a data security protection strategy based on the structured data label and the access subject information; and according to the data security protection strategy, executing a corresponding security protection operation on the access request to control the access to the target data. According to the method, the independent label knowledge base which is separated from the original data and contains the classification and grading labels is established, the classification and grading labels of the independent label knowledge base are inquired through the mapping relation, the precisely matched security policy is generated, and data security management and control based on data classification and grading are achieved.

The application provides an automatic driving video question and answer method, a model training method and a system. A training sample set is used to train an initial automatic driving question and answer model. Each sample contains continuous video image data, audio data and question text data for an automatic driving video. Video features and audio features are fused and input into a scene hypergraph generation module. Relationship features are obtained by inputting a relationship query into a relationship decoder. Driving behavior features are obtained by inputting a driving behavior query into a driving behavior decoder. Two types of classification heads output two types of classification results. A scene hypergraph embedding layer adds corresponding classification results and time step embeddings to the relationship features and the driving behavior features. After introducing identifier embeddings, scene hypergraph embeddings are obtained. The scene hypergraph embeddings and question text features are jointly input into a video question and answer module to output answer prediction values for the question text data. An automatic driving video question and answer model is obtained by constructing a fusion loss function through a Hungarian matching loss function and a cross-entropy loss function.

The invention relates to the technical field of network security, and discloses a gateway authentication method and device based on homomorphic encryption, equipment and a medium, and the method comprises the steps: carrying out the homomorphic encryption of an authentication credential plaintext, and obtaining an authentication ciphertext; constructing a gateway authentication request of the target user according to the authentication ciphertext and the request header information, performing field analysis on the gateway authentication request, and identifying whether abnormal information exists in the field analysis process; when the abnormal information exists, generating a request refusal response corresponding to the gateway authentication request, and determining an authentication state of the gateway authentication request according to the request refusal response; when the abnormal information does not exist, constructing a mapping relationship between the authentication ciphertext and the identifier of the target user, and querying a storage ciphertext corresponding to the encrypted field according to the mapping relationship; and performing ciphertext domain comparison operation on the storage ciphertext and the authentication ciphertext to obtain an operation result, and determining an authentication state of the gateway authentication request according to the operation result. According to the invention, the security during gateway authentication can be improved.

The application provides a blind scan payment method of an intelligent printer, and belongs to the field of data processing.The cash register calculates a transaction amount, generates a payment request serial number and sends the payment request serial number to a cloud server after receiving a payment instruction, establishes a first mapping relationship, and sends a voice broadcast instruction to the intelligent printer;the intelligent printer contacts the voice broadcast and starts code scanning, uploads a customer payment code to the cloud server, obtains the payment request serial number through the first mapping relationship, and establishes a second mapping relationship;the cash register starts a polling task, and sends a query request to the cloud server;the cash register and the cloud server establish a push channel, and push a payment code ready notification to the cash register through the push channel;the cash register generates a deduction request, calls a payment platform interface, and sends the deduction request to a payment platform;after the deduction is completed, a payment result is returned;the cash register generates printing data according to the payment result;and the intelligent printer outputs a transaction receipt according to the printing instruction.

This invention proposes a method, system, and storage medium for constructing a Rorschach corpus for depression screening. It collects multimodal raw data related to the Rorschach test, and performs editing and preprocessing. A core data model is constructed to store the multimodal data and their relationships. Through a data entry and import module, the multimodal data is stored in the core data model. Through a data association and retrieval module, cross-modal relational queries and a unified view are provided. Through a data export and sharing module, the data is exported in a specified structured format. Through a deep learning model integration module, the multimodal data is used for predictive analysis and stored in the core data model. The method, system, and storage medium for constructing a Rorschach corpus for depression screening provided by this invention avoid the problems existing in current Rorschach test research data management, such as poor multimodal data correlation, difficult version management, low collaboration efficiency, non-standard metadata recording, and difficulty in supporting deep learning model training.

The present invention discloses a method and device for extracting reservoir damming and interception information based on a digital elevation model, comprising: obtaining a reservoir digital elevation model and key parameters, extracting corresponding water level contour line datasets, range boundaries, and slope data; classifying the contour line datasets and performing faceting and spatial relationship operations to form different category patch datasets; querying and processing the patch datasets through spatial inclusion relationships to form a damming water area patch object set; traversing the object set, calculating the nearest point and minimum distance to the main flood control restricted water level patch or object set to form a damming and interception object, and calculating the dam top plane area, average elevation, and the lost storage capacity and affected storage capacity due to the damming and interception. The present invention overcomes the current technical problems of limited manual recognition accuracy and incomplete information extraction for damming and interception information, and provides a basis for reservoir flood control storage capacity analysis and damming and interception rectification decision-making.

The application discloses a cross-endpoint associated path retrieval method and system driven by RDF class relation, and belongs to the technical field of semantic web data association. The application carries out preprocessing on data in a SPARQL endpoint, extracts RDF class relation from an ontology and entity relation; the extracted RDF class relation is stored in a graph database in the form of graph data; when a user carries out relation query between entities, inputs a retrieval word and selects a data source; the entity URI of the retrieval word is determined, the entity URI is parsed to determine the class to which the entity belongs, and the associated path of the class is queried in the graph database; the associated path information between the classes that are queried is dynamically encapsulated into a SPARQL federated query statement; the SPARQL federated query statement is executed, and the associated path result of the query is dynamically visualized and displayed. The application can retrieve the associated path between entities across SPARQL endpoints, supports multiple data source endpoints and any associated direction, and improves the efficiency and quality of cross-endpoint associated path retrieval.

The application discloses a kind of based on query enhancement relation big model's main steam temperature prediction method and system, belong to thermal power plant thermal control and intelligent prediction field.The method utilizes multi-scale feature refining module to construct multi-resolution feature pyramid by frequency domain cycle identification and hierarchical pooling, realize the noise suppression and feature enhancement of noisy industrial time series data;Phase perception double query modeling module adopts time query and relationship query double parallel structure, respectively extracts global cycle priori and variable dynamic physical coupling dependence, and realizes feature adaptive cooperation by phase guide gate fusion;Adaptive prediction module completes main steam temperature multi-step prediction and uncertainty quantification.Through the modeling paradigm of feature refining and relationship discovery decoupling, the problem that traditional method is sensitive to non-stationary disturbance under AGC flexible peak shaving scene, it is difficult to consider prediction accuracy and robustness, provides reliable technical support for safe and economic operation of coal-fired unit.

The application provides an intelligent cloud box access method and device, equipment and a storage medium. The method is that, in response to an access operation of a user terminal, an Internet server queries an intranet access address and an extranet access address corresponding to a device identifier in the access operation according to a mapping relationship between the device identifier of the intelligent cloud box and an intranet Internet protocol address and a mapping relationship between the device identifier of the intelligent cloud box and a source Internet protocol address. The access operation is initiated by the user terminal by scanning a two-dimensional code on the intelligent cloud box, and the two-dimensional code includes the device identifier of the intelligent cloud box and the website information of the Internet server. The intranet access address and the extranet access address are sent to the user terminal, so that the user terminal accesses the intelligent cloud box according to the intranet access address and the extranet access address, and a connection is established with the intelligent cloud box.