Abstract: A system, including a plurality of node packages, an aggregator database node, and an archival database node, is provided. Each node package includes a subscriber node, an MP node, and a MaaS node. A first MaaS node selects a first set of transaction records from the first MaaS node based on a first data retention threshold and a first storage duration, and transmits the first set of transaction records to the aggregator database node for storage. The first MaaS node further controls a selection of a second set of transaction records from a third set of transaction records stored on the aggregator database node and controls a transmission of the second set of transaction records to the archival database node for storage. The selection of the second set of transaction records is based on a second data retention threshold and a second storage duration.

Abstract: This application relates to apparatus and methods for applying trained machine learning models to determine an item's relevance to a search query. In some examples, a query and data identifying a plurality of items are received. Item attributes for each of the plurality of items are obtained, and features are generated based on the item attributes. Further, a score is generated for each item by applying a trained machine learning model to the corresponding features and the query. Matching attributes are determined for each of the plurality of items based on the corresponding item attributes and the query, and the score of each of the plurality of items is adjusted based on the matching attributes. Further, the ranking data is generated based on the adjusted score of each of the plurality of items. The ranking data may be transmitted to a web server for display of the items.

Abstract: The updating of a definition layer or schema for a large distributed database can be accomplished using a plurality of data store tiers. A distributed database can be made up of many individual data stores, and these data stores can be allocated across a set of tiers based on business logic or other allocation criteria. The update can be applied sequentially to the individual tiers, such that only data stores for a single tier are being updated at any given time. This can help to minimize downtime for the database as a whole, and can help to minimize problems that may result from an unsuccessful update. Such an approach can also allow for simplified error detection and rollback, as well as providing control over a rate at which the update is applied to the various data stores of the distributed database.

Abstract: Knowledge graph systems are disclosed for implementing multiple approaches, including stand alone or combined approaches, for knowledge graph pruning. The approaches are based on graph sampling work such as, for example, information gain theory. The approaches are applied by a knowledge graph system to perform schema pruning, automatic graph pruning, and query correlation for improving query performance.

Abstract: Techniques performed by a data processing system for diagnosing problems with a communications platform include obtaining query parameters including an aggregation operator for invoking a machine learning algorithm configured to analyze performance data for the communications platform, automatically executing the query on the performance data to obtain query results by invoking the machine learning algorithm on the performance data to automatically identify a plurality of clusters of data indicative of a performance problem, and presenting a visualization of the query results. The visualization includes indicators identifying cluster properties for which the query results are further refinable and one or more second indicators identifying the second subset of the second cluster properties which are not relevant for further refining the first query results. The indicators are actuatable to automatically update and re-execute the first query based on the respective indicator that is actuated.

Abstract: Systems and methods provide a system that gathers information about data as it progresses through data processing pipelines of data analysis projects. The data analytics system derives value indicators and implicit metadata from the data processing pipelines. For example, the data analytics system may derive value indicators and implicit metadata from data-related products themselves, semantic analysis of the code/processing steps used to process the data-related products, the structure of data processing pipelines, and human behavior related to production and usage of data-related products. Once a new data analysis project is initiated, the data analytics system gathers parameters and characteristics about the new data analysis project and references the value indicators and implicit metadata to recommend useful processing steps, datasets, and/or other data-related products for the new data analysis project.

Abstract: A method for processing information includes: while performing, by a target consensus node, consensus validation on a first block, in accordance with a determination that a target consensus validation message for performing consensus validation on a second block is received: in accordance with a determination that the target consensus validation message meets a cache condition according to block attribute information of the second block, storing the target consensus validation message into a message cache pool corresponding to the target consensus node; and in accordance with a determination that the consensus validation on the first block is completed, performing consensus validation on the second block based on the target consensus validation message in the message cache pool.

Abstract: A metadata catalog may store metadata about data sources. The metadata may define table, column, partition and/or data formats, as well as title information, textual descriptions, modification information, data schemas and access information, such as location and connection information. A metadata catalog service may provide a shared, persistent, central repository for the metadata. The metadata of the catalog may be published via multiple access mechanisms and programmatically obtained and processed by other programs via the metadata catalog service. Metadata consumers may utilize the metadata catalog service to perform various metadata tasks, such as metadata retrieval, creation, addition, modification and/or deletion. The metadata catalog service may be directly integrated into existing data analytic tools as a persistent and durable metadata store allowing users to utilize the broad set of data processing tools.

Abstract: A data analysis system includes a computer configured to set a selected column selected from a plurality of columns contained in a first data set and an attribute value range selected from a plurality of attribute values contained in the selected column; extract, from the first data set, a second data set corresponding to the selected column or to the selected column and the attribute value range; analyze the second data set; and display a data image provided by visualizing the second data set and an analysis result image provided by visualizing an analysis result of the second data set.

Abstract: A system and process for tagging electronic documents or other electronic content with concepts mentioned, contained, or otherwise described in that content. Once tagged, the content may be searchable, indexable, and retrievable in order to provide that content to an end user or another recipient. The system may be configured to handle a considerable number of asset files and a large number of users, workflows, and access applications simultaneously. The system may auto-tag the content and also may include a user interface for confirming and updating those tags and for manually creating new or additional tags. Content may include documents such as medical documents relating to procedures, diagnoses, medications or other domains. Alternatively, the content may include information about various care providers, in order to allow a user to locate a physician meeting one or more desired criteria.

Abstract: Various embodiments of the present application set forth a computer-implemented method comprising detecting a tag associated with a real-world object, determining a object identifier (ID) associated with the tag, determining a first user role associated with a user of an XR environment, receiving a set of values associated with the object ID and the user role from a data source, wherein the set of values is provided by the data source based on the object ID and on a query executed on raw machine data associated with the real-world object, and displaying, by a client device within the XR environment, a visualization that displays the set of values.

Abstract: In various embodiments, methods and systems for implementing an integrated image search system are provided. The integrated image search system supports an image search feature of a content application on a mobile device. An image identifier is received to execute an image search operation. The image identifier is received via a native operating system action that is customized to support the image search feature. The native operating system action defines an entry point to the image search feature. The entry points can be based on image identifiers identified from a share image action, a share Uniform Resource Locator (URL) action, a copy share URL action, or a drag and drop action. An image of the image identifier is used to execute the image search operation to identify image search results. An image search results page having one or more images search results is caused to be displayed.

Abstract: Methods and systems for processing real-time event data by aggregating event data over various time windows and storing aggregate event data records containing the aggregated data. The method may include receiving event data at a current time, determining that the event data relates to a time prior to the beginning of a current time window, and identifying, based on the time, one or more stored aggregate event records each associated with a respective previous time window. The method may include creating, for each of the identified one or more stored aggregate event records, a new aggregate event record containing updated aggregate event data adjusted by the event data, and storing each new aggregate event record in association with its respective previous time window and a creation timestamp reflecting the current time.

Abstract: A data monitoring and evaluation system may receive a query associated with a data record from a user. The system obtains target data including a plurality of data presentations associated with the data record. The system identifies a plurality of attributes associated with the data record and maps the same with each of the plurality of data presentations for identifying a data presentation modification. The system may evaluate the data presentation modification to identify a principal data presentation. The system may determine the conformity of the principal data presentation a rule to create a principal data record. The system may determine the conformity of the principal data record to a record acceptance parameter. The system may generate a data modeling result comprising the principal data record conforming to the record acceptance parameter.

Abstract: A computer-implemented method, medium, and system are disclosed. In one computer-implemented method, an invocation request sent by an initiator is received by a blockchain node in a blockchain network. The invocation request is associated with invocation of a smart contract in the blockchain network. The smart contract includes contract code, data, and pre-update metadata. A pre-update data structure described by the pre-update metadata is parsed by the blockchain node and by execution of the contract code. The pre-update data structure is associated with the data comprised in the smart contract. Following parsing of the pre-update data structure, the pre-update data structure is represented by the blockchain node using a computer programming language. The pre-update data structure specified by the computer programming language is sent by the blockchain node to the initiator.

Abstract: A platform is provided for uniform parsing of configuration files for multiple product types. One method comprises obtaining, by a parser of a given product type, a given request from a message queue based on a metadata message of an incoming configuration file from a remote product of a given product type, wherein the message queue stores metadata messages for a plurality of product types; extracting information from the incoming configuration file based on product-specific business logic obtained from a table store comprising tables for the plurality of product types, wherein the business logic provides a mapping between information extracted from the incoming configuration file and destination database tables; and storing the contents in the destination database tables of a product-specific predefined database schema.

Abstract: A technique for providing search results may include determining a first entity type, a second entity type, and a relationship type based on a compositional query. The technique may also include identifying nodes of a knowledge graph corresponding to entity references of the first entity type and entity references of the second entity type. The technique may also include determining from the knowledge graph an attribute value corresponding to the relationship type for each entity reference of the first entity type and for each entity reference of the second entity type. The technique may also include comparing the attribute value of each entity reference of the first entity type with the attribute value of each entity reference of the second entity type. The technique may also include determining one or more resultant entity references from the entity references of the first entity type based on the comparing.

Abstract: Techniques for data replication involve: in response to a first source state machine associated with a source file system being booted up, booting up a second source state machine associated with the source file system, the first source state machine performing a first operation for resizing a first storage area of data for replication from the source file system; transmitting a resizing message from the second source state machine to a destination file system, to enable the destination file system to perform a second operation for resizing a second storage area for storing the data to be replicated into the destination file system; and in response to the first operation and the second operation being successfully performed, enabling the data for replication from the source file system to be replicated into the destination file system.

Abstract: A method provides for classifying data fields of a dataset. A classifier configured for determining confidence values for a plurality of data classes for the data fields may be applied. Using the confidence values, data class candidates may be identified. Data fields may be determined for which a plurality of data class candidates is identifiable. Using previous user-selected data class assignments, a probability may be determined for the data class candidates that the respective data class candidate is a data class to which the respective data field is to be assigned. The data fields may be classified using the probabilities to select for the data fields a data class from the data class candidates. The dataset may be provided with metadata identifying for the data fields the data classes to which the respective data fields are assigned.

Abstract: Techniques for determining a chronological order of transactions executed in relation to an object stored in a storage system are disclosed. A transaction history, stored in association with an object, includes information identifying transactions executed in relation to the object. A transaction history manager obtains information describing a state machine from a data repository. The state machine defines a finite set of states that may be assumed by objects stored in the storage system. The state machine specifies transaction types that may be executed from each state. Based on the state machine, the messaging service determines a sequence of states assumed by the object. The messaging service determines a particular transaction that is executable from each state assumed by the object. Hence, the messaging service determines a chronological order of the transactions stored in the transaction history.