12 results about "Distributed retrieval" patented technology

The invention provides an airfoil profile aerodynamic performance prediction method based on a large model retrieval enhancement generation framework, and the method comprises the steps: building a weakly-coupled database through fusing the geometric and aerodynamic characteristics of an airfoil profile, further building a strongly-coupled airfoil profile data distributed retrieval model, building the mutual cooperation of two stages of rough arrangement and fine arrangement, and achieving the prediction of the aerodynamic performance of the airfoil profile. And various characteristics of the airfoil profile are comprehensively considered, so that data can be retrieved more accurately. Meanwhile, fine-grained airfoil aerodynamic knowledge is generated in combination with a large-parameter language model, and the knowledge is optimized through knowledge distillation and fine tuning technologies. According to the method, explainable airfoil aerodynamic design priori knowledge can be excavated, rapid intelligent design of airfoils is powerfully supported, and the method has important significance in promoting the airfoil aerodynamic design to develop towards the intelligent and efficient direction.

The invention relates to the field of internet search service, and discloses a big data-based investment attraction clue analysis system, which comprises a query analysis unit, a query analysis unit, a query analysis unit, a query analysis unit and a query analysis unit, wherein the query analysis unit calls an event sequence template for defining a meta event type and a standard relative time window constraint interval; the distributed retrieval and aggregation unit is used for retrieving and aggregating meta event types to entity objects; the sequential logic verification unit is used for counting the global document frequency of the meta event, reversely mapping the global document frequency to generate a zoom coefficient, dynamically correcting a time window, and judging that only an entity object in a dynamic verification interval after correction is passed; the object sorting unit generates sorting scores according to template matching integrity, and by constructing a density and window reverse coupling mechanism, the sequential logic boundary is adaptively compressed in a high background noise environment, and the retrieval signal-to-noise ratio and the logic confidence coefficient are maintained.

This invention discloses a lightweight distributed retrieval method and system based on Dubbo. The method includes: extracting unstructured vector features from image data captured and parsed by a device or video stream; storing the unstructured vector features in a feature writing node, storing them in a file with device ID and date as a partition; setting up a retrieval module including multiple retrieval nodes to provide unstructured vector feature retrieval capabilities; setting up a routing module; and setting up a distributed retrieval management module, which, when making a retrieval request, extends Dubbo's consistent hash routing mechanism, requests the retrieval scope according to device and time partitions, and sends the unit composed of device ID and day in the request to the retrieval node calculated by the corresponding route for multi-threaded requests, with each request retrieving the top N most similar items.

The invention discloses an index recovery method, device and equipment and a computer readable storage medium, which are applied to the technical field of computers, and the method comprises the following steps: when a fault occurs, analyzing a data topological structure corresponding to an index data fragment stored by a node; based on the fragment access log of the node, calculating a heat value of the index data fragment by adopting a time decay model; determining a loading thread count according to the node resource state; determining the priorities of the index data fragments based on the business query priorities, the popularity values and the fragment memory efficiency, and determining a loading sequence according to the priorities; and according to the loading thread count and the loading sequence, loading the index data fragments in the nodes from the persistent storage to the cache, and constructing a memory finite state converter structure capable of being directly retrieved based on a data topological structure. According to the method, on the premise that the system architecture is not changed, the distributed retrieval system can be quickly recovered when the fault occurs, the unavailable time of the system is shortened, and the availability, stability and resource utilization rate of the system are improved.

The invention provides a distributed system load balancing method and device, electronic equipment and a medium. The load balancing method for the distributed system is applied to a scheduling node in the distributed system, the distributed system comprises the scheduling node and a plurality of computing storage nodes, indexes in the distributed system are decomposed into pieces and stored in the computing storage nodes, and the load balancing method for the distributed system comprises the steps that in response to an index change request, the index change request is sent to the computing storage nodes; performing an index change on the plurality of compute storage nodes; determining a first offset, a second offset and a third offset of each calculation storage node after the index is changed; and based on the first offset, the second offset and the third offset, migration of the fragments on the plurality of calculation storage nodes is carried out, so that the first offset on each calculation storage node after migration is smaller than a first threshold value, the second offset is smaller than a second threshold value, and the third offset is smaller than a third threshold value. The embodiment of the invention can be applied to various scenes such as a distributed retrieval analysis engine.

This application discloses a system optimization device, method, equipment, and medium based on a distributed retrieval system, relating to the field of computer technology. The device includes: a skew balancing strategy module for setting monitoring rules, monitoring scope, and monitoring index thresholds for the current distributed retrieval cluster; a dynamic balancing monitoring module for monitoring the skewness of the distributed retrieval cluster according to the monitoring rules, monitoring scope, and monitoring index thresholds; and a skew balancing management module for dynamically balancing and partitioning / layering management of the resource distribution and request distribution of the distributed retrieval cluster based on cluster monitoring information. This application achieves balanced optimization of the current distributed retrieval cluster by adding a skew monitoring mechanism, a skew balancing management mechanism, and a request partitioning / layering control mechanism to the sharded storage and retrieval process of the distributed retrieval system, maintaining a balance between resources and requests, thereby avoiding request anomalies and resource waste caused by skewness.

The invention provides a distributed medical image filing and desensitization system, and the system comprises a receiving and analyzing module which is used for receiving a request, analyzing and extracting a UID set, and verifying the legality of the request; the task fragmentation module is used for converting the UID set into an RDD and dividing the RDD into a plurality of partitions; the data pulling module is used for pulling a DICOM data set corresponding to the UID contained in the corresponding partition according to a preset process; the dynamic desensitization module is used for extracting metadata fields containing sensitive personal identifiers from the DICOM data set and executing corresponding desensitization strategies according to field attributes; the object storage module is used for regenerating a data stream for the desensitized DICOM data set, naming the data stream and forcibly deleting an old object; and the task monitoring module is used for recording the time consumption and the state of each UID task in the modules, writing the time consumption and the state into a distributed retrieval engine and carrying out visualization. According to the method, a PACS server component based on dcm4che3 is combined with a Spark distributed computing framework, so that distributed scheduling, desensitization and archiving processing of image archiving requests are realized.

The invention relates to the technical field of distributed storage information retrieval, in particular to a multi-source heterogeneous data retrieval method and system for marine environmental protection, and the method comprises the steps: constructing a marine data ontology library, and determining a cross-modal feature vector mapping space through a double-flow neural network; space-time reference unification is executed, and a standardized retrieval unit is packaged; enhancing the optical image based on the underwater physical model and generating a multi-modal joint index key; constructing a hybrid index structure to manage the three-dimensional spatio-temporal data; utilizing Bloom filter fingerprints and binary exclusive-OR logic to execute sea-land increment index synchronization; and generating an extended query vector based on the marine knowledge graph, and outputting a result in combination with cross-modal similarity matching and space-time constraint. According to the method, the technical defects of marine environment data modal isomerism, semantic association deficiency, non-uniform three-dimensional distribution and synchronous lag in a narrow bandwidth environment are overcome by constructing a deep fusion distributed retrieval architecture, and the retrieval precision ratio and the sea-land data collaboration efficiency are improved.

This invention relates to the field of internet search services and discloses a big data-based investment lead analysis system, comprising: a query parsing unit that calls an event sequence template defining meta-event types and standard relative time window constraint intervals; a distributed retrieval and aggregation unit that retrieves and aggregates meta-event types to entity objects; a temporal logic verification unit that statistically analyzes the global document frequency of meta-events and generates a scaling factor through reverse mapping, dynamically corrects the time window, and determines only entity objects that pass the corrected dynamic verification interval as qualified; and an object sorting unit that generates a sorting score based on the template matching completeness. This invention constructs a reverse coupling mechanism between density and window to adaptively compress temporal logic boundaries in high background noise environments, maintaining the retrieval signal-to-noise ratio and logical confidence.

The invention provides a rare disease data retrieval method and system, and belongs to the technical field of data retrieval, and the method comprises the steps of cloud data center infrastructure construction, real-time data processing and feature generation, block chain distributed storage, retrieval information knowledge mapping, distributed retrieval and data extraction, and result visual display. By constructing a block chain database containing a PBFT consensus mechanism, secure storage and tampering prevention of rare disease data are realized, and data integrity and reliability are guaranteed; a multi-algorithm fusion retrieval engine is adopted, and standardized integration of heterogeneous data, dynamic updating of a knowledge graph and accurate generation of a keyword graph and a retrieval label are achieved; through a two-stage retrieval mechanism of knowledge mapping, coarse retrieval and fine retrieval, the retrieval accuracy and efficiency are improved; and in combination with a visual display module, a retrieval result is visually presented, the efficient acquisition requirement of clinical diagnosis and treatment and scientific research on rare disease data is met, a data island is broken, and cross-domain resource sharing is promoted.

The application relates to the technical field of data processing, in particular to a semantic enhancement storage and distributed retrieval system for unstructured data. The system collects target unstructured data through a data collection module, encodes the target unstructured data through a semantic analysis module, monitors fuzzy data through a semantic enhancement module, stores the data in fragments through a semantic storage module, and acquires a distributed parallel retrieval scheme through a distributed retrieval module. The application collects target unstructured data, performs semantic analysis, semantic enhancement and data storage on the target unstructured data according to the target unstructured data, and acquires a distributed parallel retrieval scheme in real time, so that the target unstructured data semantics are enhanced, and the target unstructured data is efficiently stored and retrieved.