Abstract: Media device systems and methods are operable to identify media content events. An exemplary embodiment receives a user defined keyword tag, associates an identifier of a media content event with the user defined keyword tag, stores the user defined keyword tag and the associated identifier in a database, receives a user specification of the user defined keyword tag, conducts a search of the user defined keyword tags in the database for instances where the user defined keyword tag of the second user specification matches with the stored user defined keyword tag of the first user specification, and generates a return message that indicates the associated identifier of the media content event for each instance where the user defined keyword tag matches with the stored user defined keyword tag.

Abstract: Generating an anonymized view for a data set is described. An example method can include receiving data from a data set, wherein the data is organized in a plurality of columns. The method may also include generating a plurality of generalizations of the data. The method may also further include selecting a generalization from the plurality of generalizations using an information loss scoring function based on at least a generalization information loss. Additionally, the method may also include generating an anonymized view of the data set from the selected generalization.

Abstract: Techniques are provided for autonomous caching of hierarchical data. In one technique, query log data is stored that comprises multiple entries, each entry (a) corresponding to a different instance of a query that was executed against a database and (b) indicating a tuple (or level grouping) comprising a set of hierarchy levels corresponding to a set of dimensions. Multiple tuples indicated in the query log data are identified. For each tuple: (1) a set of entries that indicate the tuple is identified and the set of entries is associated with the tuple; (2) aggregated performance data is generated for the tuple based on performance data associated with each entry in the set of entries that is associated with the tuple; and (3) based on the aggregated performance data, it is determined whether to create a new auto-cache table or to delete an existing auto-cache table associated with the tuple.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a sparse mapping of a data hierarchy. In one aspect, a method includes accessing a data hierarchy of elements, receiving a list of identifiers that each identify an element in the data hierarchy; determining, from the data hierarchy and the list of identifiers, a minimum tree that includes each of the identified elements identified by the list of identifiers additional elements that are not identified by the list of identifiers, where the identified elements and the additional elements define a set of a minimum number of elements necessary to form a path in the data hierarchy that connects all of the identified elements identified by the list of identifiers, and where the elements that belong to the minimum tree are a proper subset of elements of the data hierarchy.

Abstract: Systems herein allow a user device to monitor calendar events with a secure bubble application. When an event is upcoming, the secure bubble application can present a notification. The secure bubble application can search other managed applications for content relevant to the meeting event. The secure bubble application can extract text, tags, and other metadata from the calendar event and any attached files. The text, tags, and other metadata can be used to search each managed application. Relevant emails, files, and notes can be displayed in a card generated by the secure bubble application.

Abstract: In general, various aspects provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for performing data discovery on a target computing system. In various aspects, a third party computing connects, via a public data network, to an edge node of the target computing system and instructs the target computing system to execute jobs to discover target data stored in data repositories in a private data network in the target computing system. In some aspects, the third party computing system may schedule the jobs on the target computing system based on computing resource availability on the target computing system.

Abstract: A method for matching supplied organizational data with trade directory information includes: receiving a data file including a plurality of organizational entries, each entry including an entity name and a geographic location; normalizing the entity name in each of the organizational entries; identifying a plurality of matching entries for each organizational entries, each matching entry including a matching name and location, and where each matching entry is identified based on a first correspondence between the matching name and the entity name and a second correspondence between the matching location and the geographic location; determining a confidence level for each of the organizational entries based on the correspondence between the first correspondence and the second correspondence for at least one of the identified matching entries; and transmitting the plurality of matching entries and determined confidence level for each of the plurality of organizational entries.

Abstract: Data replication groups may be used to store data in a distributed computing environment. The data replication groups may include a set of nodes executing a consensus protocol to maintain data durably. The nodes of the data replication groups may generate logs containing information corresponding committed operations performed by the nodes. These logs may be collected and processed to obtain useful information corresponding to the operation of the data replication group. Furthermore, this processed information may be provided in the form of a stream to enable event driven operations corresponding to the logs.

Abstract: Techniques are described for automatic creation of optimal auditable entities (AEs) using a machine learning (ML)-based clustering model. The clustering model, when executed on one or more computing devices within an audit system of a company, is configured to automatically cluster the company's business processes into AEs based on similarity analyses of business process attributes. More specifically, in some examples, the clustering model ingests business processes and their corresponding attributes from a database, automatically clusters together business processes to achieve maximum intra-cluster similarity scores, and outputs the final clusters as model AEs. The resulting model AEs may be used as functional units for internal audits of the company's business processes. The resulting model AEs may improve audit efficiency due to the model AEs including only highly similar business processes.

Abstract: A data aggregation system is described, wherein the data aggregation system may include: a plurality of sensors distributed throughout an environment; a tile database comprising a memory for storing a hierarchy of tiled layers, wherein each layer in the hierarchy of tiled layers comprises a plurality of tiles; a tiling server, the tiling server configured to: receive sensor data from one or more sensors in the plurality of sensors; assign the sensor data to a base tile in a first layer in the hierarchy of tiled layers based on one or more properties of the one or more sensors; retrieve one or more aggregate tiles from the tile database based on an identity of the base tile in the first layer, the one or more aggregate tiles each taken from one or more further layers in the hierarchy of tiled layers; determine aggregate sensor data for each of the retrieved one or more aggregate tiles based on the sensor data stored on the base layer tile; assign the determined aggregate sensor data to the corresponding one or

Abstract: A method (300) and apparatus (110, 150) collect and upload implicit analytic data. The method can include storing (320) dependency rules corresponding explicit events to implicit events. The method can include collecting (330) and storing (340) implicit event data corresponding to implicit events. The method can include receiving (350) an explicit event at the device. The method can include evaluating (360) dependency rules corresponding to the explicit event. The method can include identifying (370) a relevant subset of implicit event data corresponding to the explicit event based on evaluating the dependency rules. The method can include uploading (390) the relevant subset of the implicit event data and explicit event data corresponding to the explicit event.

Abstract: A cloud computing system, which works in cooperation with a plurality of relay devices, is configured to receive measurement data transmitted from each of the relay devices arranged in respective bases and perform accumulation processing in a hierarchical structure of a logical tree form in a measurement database, and perform aggregation analysis processing on the measurement data subjected to the accumulation processing in the respective bases and for each integration target between the bases. The aggregation analysis processing is performed on the measurement data for the each integration target between the bases by recognizing a relationship between the bases under the same starting point on the basis of a measurement unit of a measurement value or a type of a measurement source as for the value in the source accumulated in the database as an ending point of the hierarchical structure.

Abstract: Embodiments of the present disclosure are directed to systems and methods for managing a database. In one or more examples, the system obtains input data comprising one or more data entries, where each data entry comprises one or more data items, and each data item comprises a field name and a field value. The system can generate a key-value set for each data item to obtain a plurality of key-value sets. Each key-value set includes at least a first key element comprising the field name of the respective data item and a second key element comprising the field value of the respective data item. The system can sort and store the plurality of key-value sets in the database. The system can further receive a query indicative of a field name or a field value, and generate, for display, an output based on retrieved key elements sets based on the query.

Abstract: A system for managing database logging, the comprises a processor; and a user task executing in a database server process and executable by the processor, the user task to: receive in a database management system on a database server, a command to manipulate a portion of a database managed by the database management system; obtain a lock on the portion of the database; create a first log record in a first private log cache associated with the user task, the first log record recording a data manipulation to the portion of the database; enqueue the first log record to a queue; and release the lock on the portion of the database after copying the first log record to the queue.

Abstract: In some implementations, a method performed by data processing apparatuses includes receiving configuration data for a preconfigured data connector, including connection parameters, time interval parameters, and data transformation parameters. The connection parameters are used to establish a connection to a bulk data source. In response to determining that an amount of time has elapsed that corresponds to the time interval parameters, bulk data is retrieved from the bulk data source for a given time interval, and the retrieved bulk data is transformed in accordance with the data transformation parameters. Based on transforming the retrieved bulk data, a data metric is generated that condenses the retrieved bulk data. A predetermined predicted metric value is received from a prediction data source for the data metric for a time interval that corresponds to the given time interval, and the predicted metric value is stored with the measured metric value.

Abstract: The system ensures database validity by obtaining a data structure representing data processing blocks and a data flow among the data processing blocks. A first data processing block includes a first data input and the second data processing block includes a second data output. The system obtains controls associated with the data structure, where a first control corresponds to the first data output, and a second control corresponds to the second data input. The system obtains data to be processed by the first data processing block, processes the data through the first data processing block, and executes the first control based on the processed data. Based on the execution, the system determines whether the processed data satisfies the first control. If the processed data does not satisfy the first control, the system generates an alert indicating a problem with the output data validity.

Abstract: Systems and methods are provided for creating and utilizing search indexes with different properties to provide efficient and flexible means for retrieving and ranking high-dimensional content. A first index and a second index are generated with a different sets of properties, which may include a permutation prefix length and a vector quantization scheme, and are each associated with a computational workload. Further, at least one index structure may be created with a posting list associated with a permutation prefix and a set of references, rather than only a permutation prefix, to balance out posting lists of variable lengths within the index. Another embodiment of the disclosure provides for expansion of search results at search time, rather than during indexing, by retrieving posting lists associated with shorter permutation prefix after an initial list is determined to have insufficient recall.

Abstract: A method and system are provided for data synchronization. The method includes registering, in a database accessible by nodes in a cloud cluster system, node information for each node during an initialization of an application context for an application having at least one instance running on each node. The method further includes storing an update for data in (i) a local storage of a given one of the nodes and (ii) the database, responsive to a request to update the data received by the given one of the nodes. The method also includes generating a modified request that includes details for the updated data. The method additionally includes calling an application programming interface to update a state of respective local storages for the other nodes with the update responsive to the modified request, such that the update is synchronized across the at least one instance running on each node.

Abstract: Computer-implemented methods, systems and products for character string frequency analysis. The method includes a set of operations or steps, including parsing a plurality of character strings into one or more tokens, categorizing the one or more tokens into one or more token frequency categories, and generating a first similarity score between one or more pairs of character strings of the plurality of character strings. The method further includes calculating one or more degrees of commonality or rarity of the plurality of character strings based on the categorizing, generating one or more penalties for token pairs of the one or more pairs of character strings associated with the first similarity score based on the one or more degrees of commonality or rarity and the categorizing, and generating a second similarity score based the first similarity score and the one or more penalties.

Abstract: A method of implementing sub-table replication starts with the processor detecting an update to an entitlements table. The processor performs filtering of a data table based on the update to the entitlements table. The data table including an entitlements column. The processor detects an update to the entitlements column and performs incremental replication of the data table by causing a version-based replication to be executed. Other embodiments are also described herein.