66results about "Object oriented databases" patented technology

The invention provides a memory-based man-machine interaction method, electronic equipment, a medium and a program product, and relates to the technical field of artificial intelligence. Based on an interaction scene corresponding to the multi-modal interaction input information, performing long and short term memory hierarchical storage processing, memory mixed retrieval processing and / or memory active forgetting processing on the multi-modal interaction input information to obtain processed target memory data; and generating a multi-modal interaction output result based on the target memory data. By adopting the method and the device, memory-based dynamic response can be realized in human-computer interaction based on a scenarized layered humanoid memory architecture.

A solution for transforming and managing data in a data lake environment is disclosed. A definition of a transformation stream is received via a graphical user interface. The transform stream specifies an operation to transform source data into target data stored in the first format object store. And generating a virtual process corresponding to the transformation stream and storing the virtual process in a memory cloud database. A virtual process is then executed such that metadata is retrieved from the first format object store and a transform job is triggered on the compute cluster. The transform job reads the source data from the first format object store, applies one or more transforms specified in the definition of the transform stream, and writes the result to the target data in the first format object store.

In an example embodiment, a data warehousing environment, or a similar architecture, is extended to permit data storage in either an in-memory database or a Lakehouse architecture, which leverages one or more hyperscalers for the underlying storage. More specifically, a single artifact is defined in Datasphere that stores data in either the in-memory database or the Lakehouse architecture, and does so in a storage-agnostic manner.

A solution for transforming and managing data in a data lake environment is disclosed. A definition of a transformation flow is received via a graphical user interface. The transformation flow specifies operations to transform source data into target data stored in a first format object storage. A virtual procedure corresponding to the transformation flow is generated and stored in an in-memory cloud database. Then the virtual procedure is executed, causing retrieval of metadata from the first format object storage and triggering a transformation job on a computing cluster. The transformation job reads the source data from the first format object storage, applies one or more transformations specified in the definition of the transformation flow, and writes results to target data in the first format object storage.

Various embodiments of the present invention provide methods, apparatuses, systems, computing devices, and / or the like that are configured to enable effective and efficient browser event synchronization management in a federated system. For example, certain embodiments of the present invention provide methods, apparatuses, systems, computing devices, and / or the like that are configured to manage browser event synchronization using techniques that utilize object-oriented event management database stored at client computing device and asynchronous browser event processing.

Methods, systems, devices, and tangible non-transitory computer readable media facilitating assignment and / or dynamic application of a permission rule to a group of entities. In an example embodiment, the disclosed technology can: define a group of entities having a common attribute; assign a permission rule to the group of entities based at least in part on the common attribute; project the permission rule onto one or more entities in the group of entities based at least in part on assignment of the permission rule to the group of entities; obtain data indicative of a change in group membership status of an entity in the group of entities; and / or update a projection of the permission rule onto the entity to modify an association of the entity with the group of entities and / or the permission rule based at least in part on receipt of the data.

A system facilitates a process for automatically generating artificial intelligence (AI) models. The system receives a first natural language input from a user that includes a set of phrases and an instruction to analyze data associated with the set of phrases using an AI model. The system accesses a metadata graph to determine a node corresponding to the set of phrases, where nodes in the metadata graph indicate internal data objects stored in data silos. The system processes the internal data objects indicated by the determined node to generate a first set of application data. The AI model is applied to the first set of application data to generate one or more outputs. Additional user inputs can be received to modify the first set of application data and apply the AI model to the modified data, until a desired data pipeline for the model has been constructed.

Embodiments of the present disclosure relate to a spatially optimized forest for graph databases. Implementations of a graph database system for spatial optimization are provided. One implementation includes a computing system for implementing a graph database system, the computing system comprising: processing circuitry and a memory storing instructions that, when executed, cause the processing circuitry to: store a graph database comprising an initial tree graph, the initial tree graph storing a plurality of data entries, each data entry comprising a respective field identifier; receive a query to update the graph database, wherein the query comprises a request to add a new data entry; determine, based on one or more predetermined criteria, a split event to be performed; generate, by splitting out a subset of the plurality of data entries of the initial tree graph, a new tree graph corresponding to the field identifier of the new data entry, the subset of the plurality of data entries comprising all data entries of the initial tree graph corresponding to the field identifier of the new data entry; and update the new tree graph in accordance with the query.

A method for processing analytical-style queries on a transactional database is provided. A key-value database configured for point lookups and singular transactions is maintained. An analytical-style query request against the key-value database is received and analyzed to determine if it requires accessing more than a threshold amount of data. In response to a threshold, key-value data is separated into range granules covering specified data ranges. For each range granule, a snapshot file comprising key-value pairs at a specific database version and delta files specifying changes during time ranges are generated. The delta files are streamed via change feeds and buffered until accumulating a predetermined amount of mutations. The snapshot and delta files are provided to client execution nodes for parallel processing of the analytical-style query request.

Provided herein are systems and methods for collecting and processing data to assist in the processing of insurance-related tasks. The systems and methods described herein may also be useful to guiding a user such as an insurance company representative through interactions according to formalized protocols. In some embodiments, systems and methods may be used to collect and process data associated with an episode such as interaction between a user and a third party. The system may be a data collection and processing system including a knowledge representation module having one or more knowledge graphs and parsing algorithms. The knowledge representation module may be used to process structured and unstructured data and to generate one or more prompts relating to data collection and processing.

A system for automatic generation of machine learning feature definitions includes a feature schema, a user interface, a large language model (LLM), and a feature database. The feature schema defines a structured representation of a machine learning feature, including event fields, filter fields, and aggregation or categorical calculation fields. The user interface receives a natural language description of a desired feature from a user. The large language model generates, based on the natural language description and the feature schema, a candidate feature definition that conforms to the structured representation. The feature database then stores the candidate feature definition as a feature object for subsequent use in training or serving a machine learning model.

A modular object database for holistic, object-oriented business modeling, in which business data and processes of all types are represented separately in key and value objects, wherein the attributes and methods of the objects are likewise stored separately from one another, and the database management system itself is implemented as objects of the object database, as a result of which simpler handling of the object database and substantially improved data security is achieved overall.

The invention provides a data processing method and related device.The method comprises the steps that object information of a data object is obtained, and the object information comprises basic attributes of the data object; the object information is stored in a data structure, the data structure comprises a first node, the basic attribute of the data object is stored in the first node, the first node can be connected to at least one second node, and the second node is connected to the first node. Each of the at least one second node is configured to store an additional attribute of the data object.

A context navigation and action user experience framework that facilitates workflows across multiple contexts and object hierarchy levels is disclosed. Exemplary features include a switcher interface, an action toolbar with context buttons and context tabs, and a toolkit that provides an overview portal to view alerts, cross-reference information, and perform actions on objects and insights important to the user across an entire product suite.

A solution for transforming and managing data in a data lake environment is disclosed. A definition of a transformation flow is received via a graphical user interface. The transformation flow specifies operations to transform source data into target data stored in a first format object storage. A virtual procedure corresponding to the transformation flow is generated and stored in an in-memory cloud database. Then the virtual procedure is executed, causing retrieval of metadata from the first format object storage and triggering a transformation job on a computing cluster. The transformation job reads the source data from the first format object storage, applies one or more transformations specified in the definition of the transformation flow, and writes results to target data in the first format object storage.

The embodiment of the invention relates to generating embedding in an object storage system. Systems and methods are provided for automatically generating an embedding that is linked to a newly created data object through a primary key of the newly created data object. For example, in response to typing a data object into an object data structure of an object storage system, the system may automatically generate an insert that includes a primary key of the data object that links the insert with the data object. In response to receiving an update of the data object, the system may automatically identify a primary key of the data object and synchronize the embedding with the update of the data object using a notification service of the object storage system.

This invention discloses a method and apparatus for soil field surveys in an adaptive network environment. The method includes the following steps: A) Obtaining survey task information online based on the identity information of the survey equipment, including identification information of the soil survey task and a form model of the survey data; B) Constructing an offline data model based on the survey task information, generating offline survey data according to the offline data model after conducting the soil survey, and temporarily storing the offline survey data; C) Obtaining the current network connection status and signal strength of the survey equipment through network services. If the requirements are met, uploading the survey equipment identity information, soil survey task identification information, and offline survey data to the server; D) The server parses and verifies the survey equipment identity information, soil survey task identification information, and offline survey data. If the verification is successful, the data is stored in a cloud database. This invention improves data storage efficiency by connecting the cloud and the survey equipment.

The invention discloses a metadata storage method, system and device in object storage, and relates to the technical field of data storage, and the method comprises the following steps: receiving an S3 protocol interface request; according to the content of the request, calling a processing module corresponding to the request to execute metadata operation; the metadata operation comprises the steps of constructing a key for identifying metadata in the TiKV, calling a corresponding API (Application Program Interface) of the TiKV, and performing metadata reading, updating, deleting and listing operation by using the constructed key; and for the operated metadata, retrieving or storing in the TiKV through a preset key naming rule. By processing the metadata and effectively isolating the data of different business dimensions in physical storage, fine management and reliable recovery of the storage space are realized, and an extreme performance guarantee is provided for metadata retrieval in a mass data scene.

Systems and methods for generating single-node representations in graphs composed of linked nodes. The present technology enables dynamic generation of individual node embeddings in sub-linear time (less than O(n), where n is the number of nodes in the graph G), using only the PPR vectors of the individual nodes and a random projection to reduce the dimensionality of the PPR vectors of that node. In one example, the present technology includes a computer-implemented method comprising: obtaining, from a database, a graph having a plurality of nodes; generating, for a given node of the plurality of nodes, a personal PageRank vector; and producing, for the given node, an embedding vector by randomly projecting the personal PageRank vector, wherein the embedding vector has a lower dimensionality than the personal PageRank vector.

A method of generating a content library includes receiving a generate command that indicates a design application file to generate a content library, identifying a set of primitives from the design application file, and generating a content library from the set of primitives. In some cases, the method further includes receiving an import command to import content from a file that is a same format type as the content library and in response to receiving the import command, extracting appropriate values from associated primitives in the file and importing the appropriate values to the design application file. In some cases, the method further includes receiving an export command to export content from the design application file to a different application file of a specified format type and providing the content library in the specified format type.

The invention discloses a small word block micro-context vocabulary learning system. The system comprises an access layer, a monitoring and log layer, an AI and translation layer, a service module layer, a data storage layer, a middleware layer and a terminal layer which are coordinated in sequence. The access layer distributes user requests through Nginx load balancing and guarantees service stability; the monitoring layer realizes operation and maintenance monitoring by means of service monitoring and an ELK log system; the AI layer is fused with a large model to generate a micro-context, and machine translation provides multi-scene translation; the business layer supports the whole vocabulary learning process through user and order modules; the data layer adopts multiple databases to adapt to different types of data storage; the middleware layer guarantees continuous integration, distributed transactions, asynchronous communication and timed tasks; and the terminal layer supports multi-terminal access of the Web and the mobile terminal. The system solves the problems of load, monitoring, micro-context, data storage, service reliability, multi-terminal adaptation and the like in the prior art, and improves the system stability, the vocabulary learning effect and the user experience.

The application discloses a kind of knowledge graph construction methods based on data fusion, comprising the following steps: S1. construct traditional database and graph database and deep learning environment;S2. according to traditional database acquisition object;S3. screening object to obtain first data and second data, and store respectively;S4. according to public number key information acquisition third data;S5. processing second data and third data, to generate fourth data and fifth data;S6. processing fourth data and fifth data, to generate sixth data and store;S7. processing sixth data and first data, to generate knowledge graph;S8. repeat step S2 to step S7 until perfect knowledge graph.The method fuses traditional database, graph database and public number data and constructs the knowledge graph that is constantly updated, and in the construction process, by screening out error or irrelevant information, three times processing improves data accuracy, accurate and large amount of data knowledge graph can provide accurate and effective, brand-new relevant knowledge for visitor.

A method for the visualization and addressing of data within a volumetric container, using XYZ coordinates represented as a vector. Whereas users build their own immersive experience, variants, and / or representations of their respective data as polygons nested within a virtual universe. This includes variants such as time, space, velocity and trajectory as they relate to data containers, and the tracking of each user's multi-dimensional representations. This method also creates permanent threaded connections between web data, social communities and data retrieved from any other source, to a structured polygon based correlation library.

The application discloses a method and device for constructing a human-post matching information library. The method comprises the following steps: obtaining job-seeking behavior information and recruitment behavior information, and constructing a heterogeneous graph; determining first vector information of a job-seeker node and second vector information of a position node in the heterogeneous graph according to the heterogeneous graph and a target vector generation model, wherein the target vector generation model is trained based on a training sample set generated by the heterogeneous graph; storing the first vector information into a feature database and a job-seeking information retrieval library of the human-post matching information library respectively, and storing the second vector information into a feature database and a position information retrieval library of the human-post matching information library respectively, wherein the human-post matching information library is used for providing vector information of an associated node of user behavior information, and generating a matching result of an access user based on the vector information of the associated node. According to the embodiment of the application, the matching efficiency between positions and resumes can be improved, and the matching accuracy between positions and resumes can be improved.

The invention relates to the technical field of computers, in particular to a query response method, device and equipment of an entity relation network and a medium, the entity relation network is constructed based on multiple types of relation judgment data, and relation edges have multiple clear association relation types. When the query request of the specified target relationship type is received, the association state information under the target relationship type can be directly and accurately positioned and queried in the network, so that the problem that the prior art can only respond to pre-stored single relationship type query and cannot accurately respond to multi-type and multi-dimensional association relationship query is effectively solved; and the query result is more comprehensive. Moreover, the entity relationship network fusing various clear association relationship types is constructed, so that a high-quality and structured data basis can be provided for applications such as deep graph analysis, relationship-based intelligent recommendation, decision support and the like, and the bottleneck of limited analysis value of a traditional sparse network is broken through.

A method for operating a graph database, including receiving, by a computer system, a query to a particular graph database, the query identifying a plurality of vertices of the particular graph database. The method further includes performing, by the computer system, hash operations on two or more of the plurality of vertices to generate respective hash values and dividing, using the respective hash values, the query into a plurality of sub-queries, each corresponding to a subset of the plurality of vertices. The method also includes sending, by the computer system, ones of the plurality of sub-queries to a plurality of database repositories for the particular graph database.

To provide storage-independent semantic artifacts in a cloud-based data warehousing environment. [Solution] In one exemplary embodiment, a data warehousing environment, or a similar architecture, is extended to enable data storage in either an in-memory database or a lakehouse architecture, leveraging one or more hyperscalers for the underlying storage. More specifically, a single artifact is defined in Datasphere, which stores data in either an in-memory database or a lakehouse architecture in a storage-independent manner.

The application provides a data processing system for obtaining target object identification, comprising: an initial object identification combination set corresponding to a target object, a processor and a memory storing a computer program; when the computer program is executed by the processor, the following steps are implemented: obtaining a first object identification set according to the initial object identification combination set; obtaining a second object identification list corresponding to the first object identification set according to the first object identification set; obtaining a third object identification list corresponding to the target object according to the second object identification list; and obtaining target object identification corresponding to the target object according to the third object identification in the third object identification list. It can be known that, for any target object, the initial object identification combination corresponding to the target object is obtained, and the initial object identification combination is processed to obtain the target object identification, so that the target object identification obtained through the above system can avoid resource waste and is beneficial to improving the operation efficiency of the system.

Techniques are disclosed for storing and accessing data in an information model. In some embodiments, data is stored in the information model using assets, components, and relationships, or using any other suitable transformation of the data. Each asset is a container for components. Each component stores data according to a schema that defines the organization of data in the component. Assets and components can be related to other assets and / or other components. A file can be imported into the information model by extracting data from the file, creating assets and components in the information model based on the extracted data, and wiring together the created assets and components. In addition or alternatively, an application can invoke an API to write data to the information model. An application can also invoke the API to query the information model, such as to read data from the information model.

The present disclosure relates to a method for object identification based on a scalar score corresponding to a set of local microstructural features of an object. The plurality of digital images of one or more surfaces corresponding to the object is captured. The set of local microstructural features is extracted from the plurality of digital images. The plurality of objects with a set of local microstructural features is stored in a database. Local microstructural features of a query object are compared with the set of local microstructural features of the plurality of objects stored in the database using a voting function. A score is generated for individual object based on the comparison. A potential match set of the plurality of objects is selected based on the score and a status of the query object is identified based on the potential match set.