180results about "Hierarchical databases" patented technology

The present invention discloses an artificial intelligence-based adaptive big data storage and retrieval optimization system and method designed to intelligently manage and optimize large-scale distributed data environments. The system integrates data acquisition, distributed storage, metadata processing, adaptive learning, and retrieval optimization units configured to work collaboratively for continuous self-optimization. The invention employs deep reinforcement learning and predictive neural network techniques to dynamically analyze system telemetry, workload behavior, and data access patterns in real time, enabling proactive adjustment of data placement, caching, replication, and compression parameters across distributed nodes. The metadata processing framework utilizes graph-based dependency modeling to maintain semantic and contextual relationships among datasets, facilitating intelligent and context-aware data retrieval. The retrieval optimization unit interprets user queries semantically and computes the optimal retrieval route using latency prediction models and dynamic routing techniques.

A distributed indexing and resolution architecture is disclosed for decentralized systems requiring modular, trust-scoped mutation control and dynamic alias governance. The system comprises a plurality of index entries arranged in a parent-child hierarchy, each associated with a structured alias and governed by one or more anchor nodes. Anchors perform localized resolution, mutation validation, and restructuring operations under deterministic policy constraints, enabling semantic scope enforcement and entropy-sensitive adaptation without requiring global consensus or centralized control. The architecture supports scoped alias traversal, asynchronous mutation proposals, and elastic anchor registration based on system state metrics. The indexing substrate may be integrated into heterogeneous infrastructures, including systems comprising distributed software agents, semantic execution platforms, or pseudonymous identity frameworks. Anchors coordinate within defined trust domains to ensure lineage continuity, dynamic rekeying, and semantic integrity across independently governed segments of a decentralized namespace.

The invention discloses a data acquisition method and device for an energy management system, equipment and a medium. The energy management system is used for managing multiple power plants. The method comprises the following steps: creating a to-be-constructed big data platform which comprises a data acquisition layer, a data processing layer and a data storage layer; deploying a multi-protocol adapter cluster on a data acquisition layer; constructing a data standardization pipeline in a data processing layer, and generating a multi-level security label in combination with a data source security level, a service association degree and an updating frequency; a hierarchical storage framework is designed in a data storage layer and used for constructing a redundant index table crossing storage nodes and a data blood relationship graph based on a graph database; and deploying a dynamic security gateway between the data acquisition layer and the data processing layer, dynamically selecting a corresponding encryption algorithm according to the data security label, and completing the construction of a big data platform, so as to complete the data acquisition of the plurality of power plants based on the big data platform. And high-reliability, traceable and safe data support is provided for cooperative management of multiple power plants.

The invention provides a photovoltaic knowledge question-answering method, system and device based on a ReAct architecture, and relates to the technical field of photovoltaic information. The method comprises the steps that a photovoltaic industry knowledge base is obtained, original photovoltaic industry knowledge documents are processed through analysis, abstract generation and abstract vectorization, and a three-layer storage structure containing an abstract vector index table, a document metadata table and a complete document storage library is formed; obtaining a user question, initializing a ReAct cycle and creating a memory storage structure according to the user question and a retrieval tool set constructed based on the three-layer storage structure; the ReAct circulation is executed until the end, and each round of circulation comprises the steps that questions, system cue words and memory data are integrated to generate a context, a round tool and parameters are obtained through reasoning of a large language model, and accordingly the tool is called to retrieve a knowledge base, update memory and remove duplication; after the loop is terminated, an answer is generated based on the memory data. According to the method, when the photovoltaic problem is solved, the key diagnosis link and the solution can be deeply given out without omitting the key diagnosis link and the solution.

A multimodal content management system having a block-based data structure can include an artificial intelligence (AI)-based embeddings generator and indexer. After receiving an item update instruction that includes an object (e.g., a block content, a block property, or a block schema) identifier and an update payload, the system can transform the update payload—for example, by generating a chunk to capture at least a portion of the update payload. The chunk can correspond to a particular content modality included in the update payload. The system can generate and retrievably store a vector comprising a set of embeddings corresponding to the chunk, where the embeddings represent a vectorized portion of block content, block property, or block schema.

Systems and methods for modifying block items in a hierarchical structure are disclosed herein. The system can receive a request to modify a first block item. The system can query the system for information of displayed block items. The system can receive a set of identifiers of the displayed block items, relational information, and privacy information. The system can determine an indication of displayed subordinate block items associated with the first block item. The system can use the indication of the displayed subordinate block items to query a block database to obtain non-displayed subordinate block items. The system can modify the block database in accordance with the instruction, the displayed subordinate block items, and the non-displayed subordinate block items. The system can determine updated displayed block items using the modified block database. The system can communicate an indication of the updated displayed block items to the client device.

Systems and methods for machine learning-informed response and augmentation of incomplete queries and query artifacts that include executing parallel search engines in a machine learning pipeline based on an input of a query to retrieve one or more corpora of candidate digital artifacts, constructing a merged corpus of candidate digital artifacts based on the retrieved corpora of digital artifacts, ranking each candidate digital artifact of the merged corpus of candidate digital artifacts based on a computed relevance to the input query, and returning, via a user interface, a response to the input query based on a subset of prioritized candidate digital artifacts most relevant to the input query.

The invention provides a hierarchical storage method for multi-source data, a storage medium, a program product and electronic equipment, and the method comprises the steps: obtaining the multi-source data of a service, and converting the format of the multi-source data into a column storage format; performing embedded space pre-regularization processing on the multi-source data after format conversion to construct an n-dimensional simplex geometric constraint space of the multi-source data, and according to the n-dimensional simplex geometric constraint space, generating a multi-layer composite label, at least comprising a business semantic label and a cold and hot aging label, of the multi-source data; dividing the multi-source data into hot data, temperature data and cold data according to the cold and hot aging labels; the hot data, the temperature data and the cold data are stored in different storage layers respectively; and obtaining a data query request, and routing the data query request to one of the three storage layers according to the service semantic tag. The problems of semantic confusion, low storage efficiency and low access efficiency of bank data lakes in multi-source heterogeneous data fusion in the prior art are solved.

A system may receive a request to generate an object. A system may generate, based on the request, a first portion of a prompt associated with a first layer of a hierarchy and a second portion of the prompt associated with a second layer of the hierarchy, where the second layer has a lower priority than the first layer. A system may generate the object based in part on providing the portions of the prompt as input to a machine learning model, where the object is formatted according to an object format and is internally consistent. To generate the object the machine learning model does not violate instructions associated with a layer of the hierarchy based on instructions associated with a layer of the hierarchy having a relatively lower priority.

A resource dependency system displays two dynamically interactive interfaces in a resource dependency user interface, a hierarchical resource repository and a dependency graph user interface. User interactions on each interface can dynamically update either interface. For example, a selection of a particular resource in the dependency graph user interface causes the system to update the dependency graph user interface to indicate the selection and also updates the hierarchical resource repository to navigate to the appropriate folder corresponding to the stored location of the selected resource. In another example, a selection of a particular resource in the hierarchical resource repository causes the system to update the hierarchical resource repository to indicate the selection and also updates the dependency graph user interface to display an updated graph, indicate the selection and, in some embodiments, focus on the selected resource by zooming into a portion of the graph.

Systems and methods include receipt of search terms, determination of an embedding for each of the search terms, generation of a composite embedding based on the determined embeddings, determination of similarities between the composite embedding and second composite embeddings associated with each of a plurality of hierarchical group codes, determination of a hierarchical group code of the plurality of hierarchical group codes based on the determined similarities, and generation of search results based on the search terms and the hierarchical group code.

A network device is configured to (i) play back a media item indicated by a remote playback queue provided by a cloud-based computing system, (ii) receive an indication that a playback device is available for playback, (iii) display a now playing screen including (a) information identifying the media item, and (b) an icon that indicates that the network device is not in a connected state with any other network device, (iv) receive a first input selecting the icon, (v) in response to the first input, display a list of one or more available network devices including the playback device, (vi) receive a second input selecting the playback device from the list (vii) after receiving the second input, update the list to indicate that the playback device is selected for playback of the remote playback queue, and (viii) transfer playback of the remote playback queue from the network device to the playback device.

There is provided a computer implemented method. The method provides a generation of a proof of existence data structures. The method comprising: (i) receiving a request comprising a data reveal path, the data reveal path referencing a node of interest within an input hierarchical data structure (ii) obtaining the input hierarchical data structure comprising an input root node and a plurality of input nodes, wherein each of the input nodes within the input hierarchical data structure have an associated value, and (iii) generating an output hierarchical data structure based on the data reveal path and the input hierarchical data structure, wherein the output hierarchical data structure comprises a plurality of output nodes. There is also provided a method for verification of the proof of existence.

This application is directed to constructing a knowledge graph using generative artificial intelligence. A system can include one or more processors coupled with memory to identify a plurality of items of unstructured data. The system can provide, for one or more generative artificial intelligence models, a first prompt to cause the models to output a plurality of first level categories of a hierarchical data structure for the items. The system can receive the first level categories, each corresponding to a subset of the items grouped by semantic similarity, and evaluate each category according to taxonomy criteria. The system can provide a second prompt to generate second level categories for each first level category, receive the second level categories, and construct a knowledge graph data structure linking the categories and their respective subsets to relate each item of unstructured data with corresponding categories according to the hierarchical data structure.

The invention belongs to the technical field of corpus construction, and particularly relates to an AI large model corpus construction method and system based on digital experience, and the method comprises the steps: obtaining the structural data of a target problem in real time based on a constructed multi-source data obtaining channel after preprocessing and experience digitization; and then, according to the structural features of the structured data of the target problem, storing the structured data in a database in a hierarchical manner, and generating an AI large model corpus. According to the method and the device, the problem of low application efficiency of the AI large model caused by poor data quality in a corpus in the process of constructing the AI large model by an enterprise in the prior art can be solved.

Systems and methods include reception of a plurality of item descriptions associated with a respective hierarchical code which includes a plurality of group codes, extraction of a respective plurality of phrases from each item description, assignment, for each item description, a phrase embedding determined for each of the extracted respective plurality of phrases to each of the plurality group codes included in the hierarchical code associated with the item description, generation of a composite embedding for each of the plurality of group codes based on the phrase embeddings assigned to the group code, and storage of each composite embedding in association with the group code for which the composite embedding was generated.

The invention belongs to the technical field of software development, and particularly provides a research and development-oriented long and short-term memory framework construction method and system, which adopts a layered memory architecture to construct four core modules including a short-term memory compressor, a medium-term memory aggregator, a long-term memory graph and a cross-layer memory router. The system takes multi-source input such as research and development dialogues, code snippets and project documents as a starting point, extracts research and development elements through semantic analysis and entity recognition technologies, compresses lengthy dialogues into structured short-term memory by utilizing an attention distillation mechanism, upgrades high-frequency short-term memory into medium-term knowledge fragments based on a time sequence attenuation algorithm, and improves the research and development efficiency. And constructing a long-term knowledge graph containing developer portraits, project dependence and normative standards by adopting a graph convolutional network. Context understanding accuracy, multi-round dialogue continuity and personalized service quality of a large model in a research and development scene are remarkably improved, and the method is suitable for mainstream research and development tool scenes such as IDE plug-ins, code review and architecture design.

A system may identify a plurality of databases in a scope, to be included in an aggregated view, each database of the plurality of databases comprising data used to populate one or more blocks of an integrated workspace, each block comprising one or more properties, the one or more properties comprising at least one common property, wherein the scope is a grouping of hierarchically organized blocks of a render tree. A system may retrieve one or more blocks associated with each database. A system may harmonize a first database and a second database of the plurality of databases by determining a mapping of one or more of the first database to one or more properties of the second database. A system may generate the aggregated view of the one or more blocks, wherein the aggregated view includes a display of at least the at least one common property.

Various embodiments of the present disclosure provide multi-stage data lineage tracking techniques for automatically generating holistic and accurate data catalog for complex data ecosystems. The techniques may include generating a critical attribute collection for a data-related task based on one or more natural language descriptions for the data-related task. The techniques include receiving a data lineage map that defines a plurality of hierarchical data layers for a data ecosystem associated with the data-related task. The techniques include generating a critical attribute map for the data-related task by identifying a data element for a critical attribute at each of the plurality of hierarchical data layers of the data lineage map. The techniques include identifying noncritical attributes for the data related task generating a task attribute map for the data-related task based on the noncritical attributes and the critical attribute map.

Techniques for detecting service regulator failures comprising receiving time series data from a plurality of sensors in a system. Receiving hydraulic model data associated with the system. Identifying a correlation between first time series data associated with a first sensor of the plurality of sensors and second time series data associated with a second sensor of the plurality of sensors. Determining that the first sensor and the second sensor are disposed downstream of a device for controlling a pressure of a product of the system. Determining a likelihood of a failure of the device is greater than or equal to a threshold. Generating an event and displaying descriptive information identifying the event and one or more response tools for responding to the event.

A distributed data store may maintain versioned hierarchical data structures. Different versions of a hierarchical data structure may be maintained consistent with a transaction log for the hierarchical data structure. When access requests directed to the hierarchical data structure are received, a version of the hierarchical data structure may be identified for processing an access request. For access requests with snapshot isolation, the identified version alone may be sufficient to consistently process the access request. For access requests with higher isolation requirements, such as serializable isolation, transactions based on the access request may be submitted to the transaction log so that access requests resulting in committed transactions may be allowed, whereas access requests resulting in conflicting transactions may be denied.

The invention is suitable for the technical field of chips, and particularly relates to a modeling method and system for chip layout planning and related equipment.The method comprises the steps that configuration information of a chip is obtained, and a configuration file is established according to the configuration information; storing the module information in a module corresponding to the module list; establishing a multi-level nested data structure according to the module relation data; performing coordinate calculation and merging on modules of different levels in the nested data structure to obtain module coordinate data with coordinate information of all the modules; and performing shape drawing according to the module coordinate data to obtain a chip layout model. Compared with the prior art, the method has the advantages that real-time iteration can be performed according to the actual progress of chip design, designers are greatly facilitated to deeply think the chip architecture design, more accurately estimate the layout area and better determine the distribution position of the module, and the design efficiency is improved. Therefore, excessive dependence of top layer layout planning work on a traditional EDA tool is eliminated.

The invention discloses a low-altitude equipment data processing method and device and a nonvolatile storage medium. The method comprises the steps that low-altitude data collected by low-altitude equipment according to a preset data collection template is obtained through a communication base station, the low-altitude equipment is equipment with the operation height lower than the preset height, and the low-altitude data comprises equipment operation data, environment data and service data; performing data cleaning processing and format conversion processing on the low-altitude data to obtain standard data in a unified format; and performing hierarchical processing on the standard data to obtain a hot data layer, a temperature data layer and a cold data layer, storing the data in the hot data layer into an edge computing node, storing the data in the temperature data layer into a database, and storing the data in the cold data layer into a cold storage device. The technical problem that data acquired by low-altitude equipment such as an unmanned aerial vehicle cannot be uniformly processed and analyzed due to inconsistent formats of data acquired by the low-altitude equipment in related technologies is solved.

The invention discloses a hot and cold data hierarchical processing method and system for an industrial internet, and relates to the technical field of industrial internet data processing, and the method comprises the steps: constructing a first-stage hot library through a memory library meeting a first preset access speed, and constructing a second-stage hot library through a time sequence library meeting a second preset access speed, the refrigeration house is constructed through the time sequence library meeting the preset capacity; splitting the industrial internet data according to a preset particle dynamic segmentation strategy to obtain particle segmentation data; judging the particle segmentation data as to-be-reheated data or to-be-cooled data according to a preset access frequency threshold value and the particle segmentation data access frequency; and according to the to-be-reheated data and the to-be-cooled data, data migration in the first-stage heat reservoir, the second-stage heat reservoir and the cold storage is carried out. The method has the beneficial effects that the dynamic cold and hot bidirectional switching of the particle segmentation data is realized, the storage position of the cold and hot data is ensured to adapt to the access requirement of a user, and meanwhile, the data processing efficiency of the industrial internet is ensured without complicated calculation.

The invention discloses a data resource classification and level-to-level management method, system and device oriented to the energy field and a medium, and belongs to the technical field of data management in the energy field. The method comprises the following steps: acquiring a data management range comprising unstructured data and structured data; constructing an initial data directory comprising a plurality of levels according to the data management range; after the unstructured data are converted into structured data, all the structured data are stored in a pre-constructed database, and the structured data comprise data entities and keyword vectors; based on the keyword vector, classifying data entities in all the structured data by adopting a large model technology and a similarity algorithm, and storing a classification result into a corresponding classification hierarchy in the initial data directory to obtain a complete data directory; and based on the complete data directory, grading the data entities which do not reach the preset security classification to obtain a grading result. Unification of data classification and grading standards is realized, and the management efficiency is improved.

A system may identify a plurality of databases in a scope, to be included in an aggregated view, each database of the plurality of databases comprising data used to populate one or more blocks of an integrated workspace, each block comprising one or more properties, the one or more properties comprising at least one common property, wherein the scope is a grouping of hierarchically organized blocks of a render tree. A system may retrieve one or more blocks associated with each database. A system may harmonize a first database and a second database of the plurality of databases by determining a mapping of one or more of the first database to one or more properties of the second database. A system may generate the aggregated view of the one or more blocks, wherein the aggregated view includes a display of at least the at least one common property.

A system for identifying healthcare assets includes a set of tags configured to communicate with each other, the set of tags including a root tag configured to transmit an asset identifier identifying the healthcare asset and multiple component tags, each configured to transmit a component identifier identifying a part of the healthcare asset. A receiver system is configured to receive the asset identifier and the multiple component identifiers from the set of tags and to automatically generate a bill of materials (BOM) for the healthcare asset based on the asset identifier and the multiple component identifiers.

The present application belongs to the technical field of industrial detection, and particularly relates to a conveying belt laser vision tear detection system and method, comprising a layered storage architecture to construct a dynamically updated cross-model conveying belt basic database; a working condition adaptive dynamic enhancement model is designed to perform data enhancement processing on the constructed cross-model conveying belt basic database; an improved YOLOv13 vision tear detection neural network model is constructed to realize cross-model conveying belt laser vision tear intelligent detection; and a multi-dimensional three-level evaluation index system is established based on the vision tear intelligent detection result. The present application effectively improves the range, intelligent degree and detection accuracy of the conveying belt laser vision tear detection, and realizes digital quantifiable evaluation of the conveying belt tear degree.