663 results about "Graphical data" patented technology

Techniques for intelligent prefetching of database pages for improved query processing are described. Page access patterns for queries are collected over time and used to update a graph data structure to include collections of nodes corresponding to database pages that are often and / or recently accessed together. When processing a query, the graph data structure can be used to identify scenarios when prefetching may be helpful and to identify particular pages that should be prefetched. These pages are prefetched and placed in a local cache storage that can be rapidly accessed by query processors in comparison to the original storage location for this data, which may be across a network.

Training and executing machine learning pipelines for graph data sets may be orchestrated. A request for machine learning pipelines on a graph data set may be received via a machine learning pipeline building system interface. The machine learning pipeline building system may generate a profile of the graph data set from characteristics determined from the data set by the machine learning pipeline building system. Machine learning algorithms may be selected according to the profile of the graph data set and may be used to generate an execution plan that is executes the machine learning pipeline.

In a method for providing a visual representation of search results, a natural language query may be obtained from a user. The natural language query may be processed to obtain key query terms. Based on the key query terms, a relevance-ranked search on a plurality of documents may be performed to obtain a subset of the plurality of documents relevant to the natural language query. Answers to the natural language query may be extracted from relevant documents among the subset of documents, and graph data may be obtained using document links associated with the relevant documents from which the answers were extracted. The graph data may include entities and relationships identified in the relevant documents. The graph data may be used to generate a graph that may be displayed to the user to enable the user to discover information previously unknown to the user.

Processing circuitry of a learning platform may be configured to maintain a graph database describing student learners. Processing circuitry may obtain new student learner data and load the data into the graph database. Processing circuitry may receive an engagement or interaction from the new student learner and responsively extract new learnings about the new student learner which are loaded into the graph database. Processing circuitry may receive an inquiry from the new student learner and in response, extract the new student learner data and the new learnings from the graph database and contextualize, using a large language model, a learning unit from the educational content provided by the learning platform as a response to the inquiry using the new student learner data and the new learnings. Processing circuitry may further return the learning unit contextualized by the large language model to the new student learner.

The invention discloses an automatic monitoring method for infrastructure construction operation violation based on multi-modal data fusion, and belongs to the technical field of graphic data processing and pattern recognition, and the method comprises the steps: obtaining multi-modal source data of a target scene, carrying out the data recognition and standardization processing of the multi-modal source data, and generating preprocessing feature data; acquiring an on-site environment condition, and generating an environment state parameter; performing dynamic weight distribution on the preprocessed feature data based on the environment state parameters to generate weighted feature data; performing multi-source data conflict judgment and resolution on the weighted feature data to generate conflict resolution event data; and based on a preset behavior rule pattern library, performing behavior pattern matching on the conflict resolution event data to generate a violation judgment result. According to the method, a multi-modal spatial-temporal feature fusion and dynamic weight distribution mechanism is adopted, and an environment adaptive perception and multi-source data conflict resolution technology is combined, so that automatic monitoring and pattern recognition of illegal behaviors in a construction environment can be realized.

Systems and methods are provided for generating and updating a dependency graph that is used in combination with textual information about incidents to improve incident-linking suggestions. Systems and methods are also provided for generating, training, and using a machine learning model configured to perform incident linking using both graph data and text data. Beneficially, these systems and methods align the graph data and text data in order to more efficiently and accurately leverage information from the multi-modal data.

A system with graph-based Natural Language Processing (NLP) for querying, analyzing, and visualizing complex data structures is described. Such a system executes a generalized AI language model; defines and migrates a training dataset into a graph database by exposing data sources to an executing AI language model that self-defines a structure and self-writes an executable script to query the original data sources and self-writes code to load the extracted data into a graph database in the form of new nodes and new relationships with directionality between the nodes. The system further includes means for loading the extracted data into the graph database; condensing the information stored within the graph database into a condensed data structure representing the full architecture of the data in a natural language format; and responding to human language inquiries with responsive text, speech, and visualizations using the data loaded into the graph database.

A method is provided including updating a graph database based on generating one or more new nodes and edges for the graph database associated with onboarding information for a first user. The method includes extracting, from the updated graph database, extracted graph data for the first user and inputting at least a portion of the extracted graph data for the first user into one or more machine learning-artificial intelligence (ML-AI) models to obtain one or more recommended user applications. The method includes causing display of the one or more recommended user applications on a display device, receiving second user input indicating approval for granting access to at least one recommended user application from the one or more recommended user applications, and providing instructions to direct a second computing platform to grant access to the at least one recommended user application.

To provide a drawing processing device capable of appropriately selecting a requesting party for processing or estimating a processed product described in a drawing, without depending on a user's knowledge or experience. [Solution] The drawing processing device 2A includes a drawing receiving unit 202 that receives new drawing data D10 related to a processed product, and a requestee selection unit 203A that selects candidate requestees to process or estimate the processed product in the new drawing data D10 based on the new drawing data D10 received by the drawing receiving unit 202. The requestee selection unit 203A inputs the new drawing data D10 to a first learning model 220A to obtain processed product characteristic data D11 for the new drawing data D10, and inputs the processed product characteristic data D11 to a second learning model 220B to obtain processed product request data D12 for the new drawing data D10, and selects the candidate requestees based on the processed product request data D12.

The invention discloses a feature fusion processing method for anesthesia depth multi-modal data, and belongs to the technical field of graphic data processing and pattern recognition, and the method comprises the steps: obtaining a multi-modal physiological signal and an electromyographic signal of a patient; performing time axis calibration on the physiological signal to generate an alignment signal; extracting a multi-modal feature vector and calculating an anesthesia depth index; performing deviation analysis on the basis of the electromyographic signal and the index to obtain an electromyographic response deviation index; performing graphical feature mapping on the real-time electroencephalogram signal to generate a real-time time-frequency map; when the deviation index exceeds a safety threshold value, performing graph pattern matching with a pattern template library to calculate a similarity score; and outputting the current anesthesia state mode in a classified manner. According to the method, a multi-modal signal graphical feature fusion technology is adopted, and a dynamic map generation and pattern matching mechanism is combined, so that the problem of complex pattern recognition of physiological signal graphic data can be solved, and the accuracy and timeliness of anesthesia state classification are improved.

Implementations are directed to receiving graph data representative of a process-aware AAG that is representative of potential lateral movement of adversaries within a computer network, receiving risk profile data representative of a risk profile of an enterprise with respect to two or more risk aspects, generating, by a process-aware risk assessment module, a risk assessment based on the process-aware AAG and the risk profile, and generating, by a mitigation simulator module, a mitigation list based on the process-aware AAG, the risk profile, and the risk assessment, the mitigation list comprising a prioritized list of two or more facts of the process-aware AAG. Other implementations of this aspect include corresponding systems, apparatus, and computer programs, configured to perform the actions of the methods, encoded on computer storage devices.

Systems and methods are described for dynamically allocating memory for responding to requests. In some aspects, a thread may be obtained, where the thread includes a request to use a portion of system memory to perform a query of a database, such as a graph database. The system may determine that the portion of memory is greater than available memory of a maximum managed memory size of the system, and may block the thread until additional memory becomes available. The maximum managed memory size may be configurable, and may be less than a total memory of the system. The system may then determine, based at least in part on a change in the available system memory, that the available system memory is equal to or greater than the portion of memory to satisfy the request, and cause the system to process the thread to provide a response to the query.

A method is disclosed, the method comprising the steps of receiving, from a first client application, first graphical data comprising a first node; receiving, from a second client application independent of the first client application, second graphical data comprising a second node; and generating a scenegraph, wherein the scenegraph describes a hierarchical relationship between the first node and the second node according to visual occlusion relative to a perspective from a display.

The various implementations described herein include methods and devices for providing an instant messaging interface for data analytics. In one aspect, a method includes displaying a user interface for a communication application, including displaying a shared link to a graphical data visualization. A snapshot button near the link is used to generate a link snapshot comprising a version of the graphical data visualization. In response to user activation of the snapshot button, the method generates the link snapshot. To generate the link snapshot the method first determines if the user or users have proper security access to view the data contained in the graphical data visualization. If a user has proper security access to a subset of the data from the data source, the method dynamically generates the link snapshot for the subset of data to which the user has security access.

The invention discloses a real estate registration information real-time query system based on graphic data, and relates to the technical field of information real-time query, and the system comprises a knowledge graph generation unit which is used for processing an established multi-modal data set, generating a joint vector, coding the joint vector, and storing the coded joint vector in a preset graph database, synchronously constructing a dual dynamic index mechanism to generate a real estate knowledge graph; the knowledge graph updating unit is used for capturing change events in the multi-modal data set in real time, identifying graph structure differences of a change area and generating a topology correction strategy by positioning the change area and a neighborhood range, and updating a real estate topology knowledge graph in combination with transaction characteristics of a graph database; a query result display unit; and a data synchronization unit. According to the method, the real-time data channel is constructed, capturing and incremental processing of the real estate business change event are achieved, and it is ensured that the real estate knowledge graph and graphic data are dynamically consistent in topological structure and attribute information.

Embodiments of this specification provide a method and an apparatus for generating a text corpus by using a knowledge graph. Graph elements of the knowledge graph include a node representing an entity and a connecting edge representing a relationship between nodes. Privacy data can be organized into structured data by using the knowledge graph. The graph data includes several triplets including graph elements in the subgraph, and the ontology information includes at least a type of each graph element in the subgraph. Several sentences are generated based on several pre-constructed sentence templates, the graph data, and the ontology information. The several sentences are classified into a generated sentence set, and at least one of the several sentence templates is constructed based on the ontology information. A text corpus corresponding to the subgraph is determined based on the generated sentence set. The text corpus is used to train a language model.

The invention relates to the technical field of industrial internet of things operation and maintenance, and particularly provides a remote maintenance auxiliary method integrating video monitoring and three-dimensional modeling. The method comprises the following steps: acquiring engineering graphic data and point cloud scanning data of maintenance equipment, and collecting video stream data of a maintenance equipment site; the video stream data is used for describing the operation state of maintenance equipment; the video stream data comprises a plurality of video frames; matching the point cloud scanning data with the engineering graphic data, and constructing a watertight three-dimensional grid model according to a matching result; mapping texture features of the maintenance equipment in a target video frame to the surface of the watertight three-dimensional grid model to obtain a target three-dimensional model; and receiving a first maintenance instruction marked in the target three-dimensional model by a remote expert, and sending the first maintenance instruction to a video picture of a client of an on-site maintainer. According to the technical scheme provided by the invention, the time consumption for positioning the overhaul part can be reduced.

In one implementation, a device may facilitate the hunting, detection, and forensic assessment of threats utilizing a knowledge graph. The device obtains telemetry data collected within a cloud computing environment. The device forms a temporal graph that represents changes in the cloud computing environment over time based on the telemetry data. The device maps the temporal graph into a knowledge graph for storage in a graph database. The device makes the graph database available to an artificial intelligence model that issues queries to detect security threats to the cloud computing environment.

An architecture of a multi-cloud inspector for any computing device type is provided. According to an embodiment, a method for implementing multi-cloud inspection includes accessing an object list, determining which objects to inspect, determining which inspectors to use, creating object copies, providing and running inspectors for each object copy, receiving inspection report summaries, generating an enriched dataset, and adding the enriched dataset to a security graph database.

The embodiments of the present application relate to the technical field of terminals. Provided are a rendering processing method and an electronic device. The method comprises: determining a plurality of rendering instructions corresponding to first graphic data to be rendered of a first application program, wherein the plurality of rendering instructions include a first rendering instruction; and then reading, from a graphics processing unit (GPU) memory, a first rendering resource corresponding to the first rendering instruction, and executing the plurality of rendering instructions on the basis of rendering resources respectively corresponding to the plurality of rendering instructions, so as to render the first graphic data. In this way, a rendering resource is read from a GPU memory, so as to reduce data interaction between a GPU and a main memory, thereby reducing the bandwidth consumption of a terminal device.

The invention discloses an intelligent generation and application method and system for structural data of an engineering drawing, and the method comprises the steps: obtaining the engineering drawing, analyzing the engineering drawing, and determining a data relation, graphic data, text data and image data reflected by the engineering drawing; screening, identifying and combining the data relationship, the graphic data, the text data and the image data to obtain a drawing object, a component object and a space object; and outputting engineering drawing structured data based on the drawing object, the component object and the space object, and applying the engineering drawing structured data. According to the method, the engineering drawing is analyzed and the data of the engineering drawing is structured, so that the processing efficiency and accuracy of the engineering drawing are improved.

Systems and methods are provided for generating an index of a set of vectors as a distributed proximity-based graph data structure comprising representative vectors corresponding to subsets of the set of vectors, storing the set of vectors across a plurality of storage devices of a distributed storage system based on the distributed proximity-based graph data structure, and loading, in response to a vector query, a plurality of subsets of the set of vectors from the distributed storage system based on the distributed proximity-based graph data structure.

A method including providing a graph database representation, wherein the graph database representation represents a plurality of nodes in a graph which are interconnected by respective edges, wherein each node of the plurality of the nodes represents a data sample and is assigned to at least one node feature, wherein each edge of the plurality of the edges represents a relationship between the data samples, transforming the graph database representation into a data matrix using a first machine learning algorithm suitable for graph data and an architecture as first layers of a joint machine learning architecture, determining at least one node of the plurality of nodes based on the transformed data matrix using a second machine learning algorithm and a second architecture as second layers of a joint machine learning architecture, and providing the at least one determined node. Further, a computing unit and a computer program product is provided.

The invention provides an interface display method and electronic equipment, the method is applied to the electronic equipment, the method comprises the steps that multiple groups of first data are obtained, each group of first data in the multiple groups of first data comprises the layout, style and content of a fast application card, and all groups of first data in the multiple groups of first data are different; converting each group of first data in the plurality of groups of first data to obtain a plurality of groups of first commands and a plurality of groups of first data resources; generating a plurality of graphic data according to the plurality of groups of first commands and the plurality of groups of first data resources; based on the multiple pieces of graphic data, a first interface is displayed, and a dynamic picture corresponding to the fast application card obtained according to the multiple pieces of graphic data is displayed in the first interface. Therefore, the process of displaying the first interface and the dynamic picture of the fast application card is relatively efficient, the dynamic picture is prevented from being blocked as much as possible, and the visual experience of a user is ensured.

The invention relates to the technical field of data processing, in particular to a GPU intelligent scheduling method, system and device and a medium, and the method comprises the steps: obtaining game scene information, carrying out the task recognition and classification of the game scene information, and obtaining the classification data information; constructing a load prediction model, and inputting the classified data information into the load prediction model to obtain load prediction result information; carrying out reinforcement learning processing on the load prediction result information to obtain reinforcement prediction result information; and load distribution processing is carried out according to the enhanced prediction result information, dynamic adjustment information acting on the GPU is obtained, load balancing is realized in a high-complexity scene, and the graphic data processing efficiency is improved.

The invention relates to the technical field of system application, and discloses an online document processing method and system based on structured storage, and the method comprises the steps: splitting content elements of an online document into blocks, and carrying out structured storage as independent objects; querying basic information of the document, loading data according to a document block pageBlockId list, creating a component according to the loaded data, constructing a component tree, and performing document rendering by using a lazy loading technology; the method comprises the following steps: abstracting documents and document blocks as objects, synchronizing the objects to a graphic database, modeling a relationship between the documents and the document blocks as an edge in the graphic database, and converting the relationship between the documents into a graphic data structure; when the document content changes, the storage interface is called to store the changed document block, and the online document is automatically stored, the document content is structurally stored in the block form, dynamic updating of the online document is achieved, the reference relation between the documents is stored and managed, and the relation between the documents is visually and clearly displayed.

The invention discloses a whole industry chain tracing method and system for traditional Chinese medicine decoction pieces and a medium, and the method comprises the steps: obtaining a tracing two-dimensional code image corresponding to a to-be-traced traditional Chinese medicine decoction piece, and carrying out the preprocessing, thereby obtaining a preprocessed image; watermark information carried by the preprocessed image is extracted, after the watermark information is judged to be effective information, traceability data is searched, the traceability data at least comprises planting data, harvesting and processing data, logistics storage data and circulation data, and the planting data further comprises environment data; and transmitting the traceability data to a scanning terminal for display, thereby completing the whole industry chain traceability of the to-be-traced traditional Chinese medicine decoction pieces. The method belongs to the technical field of data processing, the watermark information is read through the graphic data to reflect the authenticity and validity of the traceability two-dimensional code image, the traceability data is set to contain the environmental data reflecting the influence of the environmental factors on the traditional Chinese medicinal materials in the planting process, the traceability is ensured to be true and effective, and meanwhile the traceability efficiency is improved. And the traditional Chinese medicine decoction pieces are accurately and comprehensively traced in the whole industry chain in combination with environmental factors.

Disclosed is a mutually generative artificial intelligence system based on multi-dimensional spatiotemporal information vector graphics, relating to the field of artificial intelligence and engineering applications. Based on a geographic information system (GIS) or a computer-aided design (CAD) platform and a data source, a multi-dimensional vector spatiotemporal large model terminal, a multi-dimensional spatiotemporal information processing agent terminal, and an intelligent information system application terminal are constructed. For multi-dimensional spatiotemporal data such as two-dimensional and three-dimensional vectors and temporal states, a multimodal spatiotemporal large model having an understanding capacity for an engineering professional knowledge system, a data processing flow, multi-dimensional vector graphics, and thematic graphics-text documents is pre-trained to achieve the mutual expression and generation of engineering multi-dimensional vector graphics and thematic graphics-text documents and to form an intelligent engineering graphic data processing application.

An apparatus and method for the generation and improvement of efficiency data is disclosed. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor. The memory instructs the processor to receive a user profile from a user, wherein the user profile comprises occupational data. The memory instructs the processor to determine efficiency data as a function of the occupational data. The memory instructs the processor to generate a plurality of graphical data as a function of the efficiency data. The memory instructs the processor to identify a plurality of efficiency clusters associated with the efficiency data as a function of the plurality of graphical data. The memory instructs the processor to identify an ideal arrangement of each cluster of the plurality of efficiency clusters as a function of the efficiency data and generate improvement data as a function of a comparison.