Abstract: An embodiment enables a first machine to receive an asynchronous data update from a second machine, the asynchronous data update comprising a first stream of identifiers and a second stream of data, wherein the first stream of identifiers comprises a first identifier corresponding to a first data segment in the second stream of data. An embodiment analyzes, as a part of the asynchronous data update, the first stream of identifiers. An embodiment determines at a first time, responsive to the analyzing, that the first data segment corresponding to the first identifier has not arrived at the first machine by the first time. An embodiment updates, responsive to the determining at the first time, a record at the first machine with the first identifier. An embodiment updates the record at a second time, responsive to receiving the first data segment at the first machine at the second time.

Abstract: In some implementations, a user device may transmit, to a first data source, a first message encoding a first query and may receive a first response to the first query from the first data source. The user device may transmit, to a second data source, a second message encoding a second query that duplicates the first query and may receive a second response to the second query from the second data source. The user device may transmit a first reverse query to the first data source based on the second response and/or a second reverse query to the second data source based on the first response. The user device may receive at least one reverse query response. Accordingly, the user device may determine whether an answer to the first query is valid, based on the first response, the second response, and the at least one reverse query response.

Abstract: Arrangements for controlling data retrieval are provided. In some aspects, a data request may be received by a computing platform. A pre-fetch engine may be executed to analyze the data request and generate, using a machine learning model, a pre-fetch template identifying data sets responsive to the request. The pre-fetch template may be transmitted to one or more data repositories and response data sets including data use parameters may be received. The received plurality of data sets may be analyzed to determine whether a triggering action has occurred. If a triggering action has occurred, one or more data modification functions may be performed. For instance, data may be deleted, prevented from further processing, or the like, in response to detection of a triggering action.

Abstract: In this approach, a system and workflow are provided for generating unique content identifiers (sometimes referred to herein as “Content IDs”) for digital assets. A Content ID is uniquely associated with each piece of content within a customer's asset space The Content ID need not be based on the contents of the asset (such as pixel values of an image), and both perceptual and non-perceptual aspects of identification of the asset may be evaluated to enable different permutations of the same digital asset to have different Content IDs. The system provides for content similarity detection by identifying a content match and surfacing this match within a customer data set, providing automated, scalable, and consistent Content IDs for multiple use cases associated with a digital asset management solution.

Abstract: A cellular network having radio access network (RAN) nodes where each RAN node includes (i) a central unit (CU) that resides on a public cloud of the cellular network, (ii) a distributed unit (DU) that resides on a private cloud of the cellular network such that the DU is in communication with the CU on the public cloud of the cellular network, and (iii) a radio unit (RU) under control of the DU. The cellular network also has network repository functions (NRFs) that are distributed on the cellular network and reside on at least the public cloud of the cellular network where the NRFs control operation of cell sites and local data centers (LDCs) on the cellular network. The network also has processors configured to control data collection edge applications residing with the NRFs that are distributed on the cellular network.

Abstract: A computer-implemented method can receive a message sent from a source entity, perform first pre-processing operations for verifying validity of the message, perform second pre-processing operations for determining a category of the message, extract metadata from the message, generate an enriched message comprising the metadata and the determined category, perform post-processing operations for classifying the enriched message into one of a plurality of event types, broadcast the enriched message to a message broker, and routing, by the message broker, the enriched message to one or more target entities registered an event type into which the message is classified.

Abstract: An updating method of a citation document, an apparatus, an electronic device and a storage medium. The method includes: acquiring a document relationship diagram of a database; acquiring a document modification instruction, where the document modification instruction includes a document identification and a document modification content; extracting an associated document identification from the document relationship diagram according to the document identification; pushing the document modification content to an associated document corresponding to the associated document identification.

Abstract: Techniques for database management are described. A database management system may transmit a request for a data management system of a database to provide a set of metadata attributes for structured data within the database, and may receive a set of metadata attributes for the structured data within the database. The data management system may perform a pattern matching procedure to evaluate the set of metadata attributes for the structured data within the database against one or more patterns associated with a data type to determine one or more locations within the database that include structured data of the data type. Based on the pattern matching procedure, the data management system may output an indication that the one or more locations within the database include structured data of the data type.

Abstract: Methods and systems for managing and use of data are disclosed. To manage data, the data may be classified with respect to topics that are relevant to a user of a data storage system. The topics that are relevant to the user may be identified based on digital recordings of conversations between the user and other persons. Over time, the topics that are relevant to the user may change. The changes in relevant topics may be used to identify occurrences of different events in the user's life. These life events and data classified for corresponding topics may be used to service information request by providing context for the data and a means of discriminating more relevant from less relevant data.

Abstract: Data are maintained in a distributed computing system that describe a graph. The graph represents relationships among items. The graph has a plurality of vertices that represent the items and a plurality of edges connecting the plurality of vertices. At least one vertex of the plurality of vertices includes a set of label values indicating the at least one vertex's strength of association with a label from a set of labels. The set of labels describe possible characteristics of an item represented by the at least one vertex. At least one edge of the plurality of edges includes a set of label weights for influencing label values that traverse the at least one edge. A label propagation algorithm is executed for a plurality of the vertices in the graph in parallel for a series of synchronized iterations to propagate labels through the graph.

Abstract: A high-performance distributed ledger and transaction computing network fabric over which large numbers of transactions are processed concurrently in a scalable, reliable, secure and efficient manner. In one embodiment, the computing network core is configured to support a distributed blockchain network that organizes data in a manner that allows communication, processing and storage of blocks of the chain to be performed concurrently at very high performance and low latency, even when the transactions themselves originate from distant sources. This data organization relies on segmenting a transaction space within autonomous but cooperating computing nodes that are configured as a processing mesh. The system also provides for confidence-based consensus. A configuration system is provided to enable configuration updates to be securely implemented across various subsets of the computing nodes.

Abstract: Aspects of a data environment, such as the creation, provisioning, and management of data stores and instances, are managed using a separate control environment. A user can call into an externally-facing interface of the control environment, the call being analyzed to determine actions to be performed in the data environment. A monitoring component of the control plane also can periodically communicate with the data environment to determine any necessary actions to be performed, such as to recover from faults or events in the data environment. A workflow can be instantiated that includes tasks necessary to perform the action. For each task, state information can be passed to a component in the data environment operable to perform the task, until all tasks for an action are completed. Data in the data environment can be accessed directly using an externally-facing interface of the data environment, without accessing the control plane.

Abstract: One example method includes receiving a set of database parameters, creating one or more simulated databases based on the database parameters, receiving a set of target characteristics for the database, based on the target characteristics, slicing a datastream into a grouping of data slices, populating the simulated database(s) with the data slices to create the database collection and forward or reverse morphing the database from one generation to another without rewriting the entire database collection.

Abstract: An example method includes receiving by a server and from a computing device a natural language-based query, converting the natural language-based query into an embedding formatted query having a vector format, inputting the embedding formatted query into a machine-learning logic model, and determining by the machine-learning logic model a query response to the embedding formatted query that is predicted by the machine-learning logic model to be in context of beauty or cosmetic industry. The machine-learning logic model is trained using a multi-dimensional learned-embedding that includes semantically similar terms in proximity in an embedding space and the embedding space is limited to salient terms associated with the beauty or cosmetic industry. The method also includes communicating by the machine-learning logic model the query response to the computing device.

Abstract: One example method includes, beginning at a parent node of a data structure, calculating a first W-index for the parent node and a left child node, calculating a second W-index for the parent node and a right child node, when the first W-index exceeds a threshold ?, marking the left child node as a candidate to be included in a sub-cluster separate from a sub-cluster that includes the parent node, when the second W-index exceeds the threshold ?, marking the right child node as a candidate to be included in a sub-cluster separate from the sub-cluster that includes the parent node, and recursively calculating respective W-indices for all other parent nodes in the data structure until all child nodes of the data structure have been assigned to a sub-cluster.

Abstract: The subject technology generates, by a database system, cell data for a particular table based on values from a source table, the values being based on raw input data, the source table comprising multiple rows and multiple columns, the raw input data comprising values in a first format, the values comprising input features corresponding to datasets included in the raw input data for machine learning models, the source table being provided by an external environment, the external environment comprising an external system from the database system. The subject technology performs a database operation to generate the particular table including table metadata, column metadata, and the generated cell data, the generated particular table comprising a second format that causes more efficient processing of data by the database system using a single query on the particular table compared to processing the raw input data from the source table.

Abstract: Mobile computing network queried content capture is performed by receiving, from a server, a task executable by a mobile computing network, and a retention policy, executing the task using the mobile computing network to capture target content, assigning, to a first instance of captured target content, a probability of reducing based on the retention policy, reducing, in response to an amount of available storage becoming equal to or lower than a threshold amount, at least one of the first instance and a portion of other stored data based on the probability of reducing, and transmitting, in response to connecting to a wide area network, each instance of captured target content.

Abstract: Embodiments predict errors using database validation rules. Validation rules can be defined that include business logic for validating transactions performed on a database with a data model. Transactions can be performed using the database, where the database is in a post-transaction state after performance of the transactions. The database can be validated in the post-transaction state by performing the defined business logic for a subset of validation rules, where at least one validation rule fails to validate. Using a trained machine learning model, one or more errors for one or more future transactions can be predicted, the predicted errors being based on the at least one failed validation rule.

Abstract: According to an aspect, a computer-implemented method for improving query performance in a databased management system (DBMS) includes receiving, by a query optimizer of the DMBS, a query for execution. The method also includes creating, by the query optimizer, an initial access path for the query based on state and executing the query based on the initial access path. The method further includes observing, by a query agent of the DBMS, the execution of the query and modifying at least one of the state based on a determination by the query agent that a change to the initial access path would improve the execution of the query.

Abstract: A system includes an interface and a processor. The interface is configured to receive a table indication of a data table and to receive a transaction indication to perform a transaction. The processor is configured to determine a current position N in a transaction log, determine a current state of the metadata; determine a read set associated with a transaction; attempt to write an update to the transaction log associated with a next position N+1; in response to a transaction determination that a simultaneous transaction associated with the next position N+1 already exists, determine a set of updated files; and in response to a determination that there is not an overlap between the read set associated with the current transaction and the set of updated files associated with the simultaneous transaction, attempt to write the update to the transaction to the transaction log associated with a further position N+2.