113results about "Object oriented databases" patented technology

The invention relates to the field of financial science and technology, and particularly discloses a cross-platform financial data integration and real-time analysis system and method. The system is characterized in that a distributed heterogeneous data acquisition module accesses multi-source data in parallel through a pluggable protocol adapter; the streaming data cleaning engine realizes field-level normalization based on a dynamic template and semantic mapping; the hybrid storage architecture forms a three-level system by a memory database, a time sequence database and distributed file storage; the stream processing core engine adopts an elastic sliding window to execute CEP complex event processing; and the dynamic analysis decision module integrates online machine learning to generate a real-time transaction signal. The method comprises the steps of multi-source concurrent acquisition and microsecond-level timestamp injection, context sensing data standardization, dual-channel data storage, event time window aggregation, dynamic risk calculation and block chain audit evidence storage. The defects of low data fusion efficiency, high real-time analysis delay and the like in the prior art are overcome, and cross-platform data processing timeliness and decision accuracy are remarkably improved.

The invention provides an SQL (Structured Query Language) statement generation system, a multi-source knowledge base cluster module comprises a plurality of vector libraries, each vector library is used for storing a data vector of a data type corresponding to the vector library, a query understanding module can analyze and process a natural language query problem input by a user after receiving the natural language query problem, and the query understanding module can obtain a query result. According to the technical scheme, the vector engine module can perform collaborative retrieval on at least one vector library according to the processed query problem to obtain the target data information, multiple data types are respectively stored in different vector libraries, so that only the vector libraries related to the processed query problem need to be retrieved, and the retrieval efficiency is improved. According to the method, the retrieval accuracy is improved, multiple vector libraries correspond to multiple data vectors of different data types, and the accuracy of the generated SQL statements can be improved.

The invention provides a data synchronization optimization method and system based on metadata version control, and the method comprises the steps: responding to the change of metadata of a barrel in a source site, generating a metadata synchronization log, and recording the version number of the barrel in the metadata synchronization log; pulling the metadata synchronization log from a site, and analyzing the metadata synchronization log to obtain a version number of the bucket; if the metadata of the bucket does not exist in the slave site or the version number of the bucket in the slave site is smaller than the version number recorded in the metadata synchronization log, stopping the current data synchronization operation, and adding the data synchronization task of the bucket into a data synchronization retry queue; and in response to the fact that the metadata version number of the bucket is consistent at the master site and the slave site, allowing the slave site to continue to execute the data synchronization operation of the bucket. Through combination of various technologies, the version of the metadata is automatically identified, so that the object is synchronized to the correct target bucket.

The described technology pertains to a distributed computing environment, specifically implementing a streaming protocol on a scalable object storage service. The technical problem addressed is the high computing resource demand of distributed streaming platforms. The solution involves separating content from location metadata, allowing centralized, scalable storage of metadata. Brokers store content in object storage services based on specific metrics, such as fast read / write times or greater storage capacity. A background platform remaps metadata sequences based on logical timestamps, optimizing data retrieval. This system enhances the efficiency of computing resources by reducing the load on brokers and improving data access speeds. A use can be in cloud computing systems for efficient content streaming and storage management.

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.

The invention provides a database index implementation method based on object storage, which is used for solving the problem of efficient retrieval when object storage is used as a database storage engine. According to the method, a special index storage structure is constructed in object storage and comprises an index metadata area and an index data area, and index data is organized through a segmentation management mechanism. Each segment in the index data area comprises a Bloom filter file, an index entry file and a segment abstract file, and efficient organization and access of index data are achieved. According to the method, a batch writing and parallel retrieval strategy is adopted, and a segment merging and garbage collection mechanism is matched, so that the index performance and the storage efficiency are ensured. The method has the beneficial effects that the query performance when the object storage is used as the database is remarkably improved, the storage overhead is reduced, meanwhile, the data consistency is ensured, and a key technical support is provided for realizing a database system based on the object storage.

A system for managing versioning of ontology data represented in multiple forms respectively in multiple databases and related methods are disclosed. The system is programmed to determine which changes to the ontology are to be incorporated into a new version of specific ontology data. In response to a write request to write a latest version of specific ontology data, the system is programmed to start representing the latest version in the multiple databases according to a first predetermined strategy. In response to a read request to read a latest version, the system is programmed to return a particular version from at least one of the multiple databases according to a second predetermined strategy.

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.

A system, method, and computer-readable medium for performing a data center monitoring and management operation. The data center monitoring and management operation includes: generating a tag for an object within a data center asset, the tag for the object associating a contextual meaning with the object; registering the tag when the tag is generated; storing the tag within a tag storage repository when the tag is registered; and, managing an aspect of the tag via a data tag management operation.

The invention relates to the technical field of artificial intelligence, discloses a business risk prediction method and device for setting and adjusting a risk threshold value based on a profit and loss balance point, equipment, a medium and a product, and aims to solve the problems that the balance of cost and profit is not considered, dynamic adjustment capability is lacked, the risk threshold value cannot be dynamically adjusted, and the risk threshold value cannot be dynamically adjusted in the prior art. And the accuracy and flexibility of credit risk control are poor. The method comprises the following steps: constructing an initial prediction model, and collecting and training the initial prediction model based on historical business data to obtain a business risk prediction model; calculating a profit and loss balance point of the business based on the historical business data, and setting an adjustment risk threshold based on the profit and loss balance point; and obtaining a to-be-predicted target service, calling the service risk prediction model to perform service information prediction on the target service, obtaining a service information prediction value, comparing the service information prediction value with the set and adjusted risk threshold, and determining a final service risk result. According to the method, the accuracy and flexibility of the business risk prediction method are improved.

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.

A computer-implemented method comprises applying at least one processing action to at least one source data object, and responsive to applying the at least one processing action, generating one or more derived objects from the at least one source data object. For each derived object, the method comprises storing the derived object in a first data store, determining association information for the derived object and the at least one source data object from which the derived object is generated, and writing the association information in a second data store to associate the derived object with the at least one source data object, such that an origin of the derived object can be determined. Responsive to modifying the at least one source object, the method further comprises creating at least one modified object, and for each derived object of the at least one source object: writing new association information between the derived object and the at least one modified object, and removing previous association information between the derived object and the at least one source data object, or generating a new derived object from the at least one modified object and writing new association information to associate the new derived object with the at least one modified object.

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.

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

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.

The invention discloses a soil field investigation method and device adaptive to a network environment. The method comprises the following steps: A, acquiring survey task information on line according to identity information of survey equipment, wherein the survey task information comprises identification information of a soil survey task and a form model of survey data; b, constructing an off-line data model according to the survey task information, performing soil survey, then forming off-line survey data according to the off-line data model, and temporarily storing the off-line survey data; c, acquiring the current network connection state and signal strength of the investigation equipment through network service, and if the requirements are met, uploading the identity information of the investigation equipment, the identification information of the soil investigation task and the offline investigation data to a server; and D, the server analyzes and verifies the identity information of the investigation equipment, the identification information of the soil investigation task and the offline investigation data, and stores the information in a cloud database if the verification is passed. Through the cloud and the investigation device, the data storage efficiency is improved.

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.