Abstract: Disclosed in some examples are methods, systems, machine-readable media, and devices which provide for real-time personalized suggestions for participants in a network-based communication service. The personalized suggestions may include options for taking actions, content suggestions, and smart replies. These suggestions may be based upon the current conversation and are delivered personally to each participant.

Abstract: Embodiments are described for performing an uninterrupted backup in a storage system responsive to an abort event. A backup agent receives a plurality of file objects to be backed up on a target device during a first backup session. The backup agent initiates a parent interrupt service routine (ISR), which generates a plurality of child ISRs. Each of the plurality of child ISRs monitors a backup state of a corresponding file object. The parent ISR generates a virtual file object queue (VFOQ) to store a current backup state of each of the plurality of file objects. When an abort occurs, the current backup state of each of the plurality of file objects is saved in a respective child ISR of that file object. During a subsequent backup session, backup of the plurality of file objects commences based on the current backup state of each of the plurality of file objects.

Abstract: A computer-implemented method for efficiently backing up large datasets may include (i) identifying data on an application server to be deduplicated by a deduplication server and then stored on a backup server, (ii) dividing the data into subsets, and (iii) for each subset of data subsequent to an initial subset of data, (a) transferring the subset of data to the deduplication server in response to detecting that a previous subset of data has completed transfer to the deduplication server, (b) deduplicating the subset of data in response to detecting that the previous subset of data has completed deduplication, and (c) transferring a deduplicated version of the subset of data to the backup server in response to detecting that the subset of data has completed deduplication and the previous subset of data has completed transfer to the backup server. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Methods, systems, and media for presenting related media content items are provided.

Abstract: A live image of a virtual machine is disclosed. When generating a live image, an image of a virtual machine is generated. A journal is also generated that starts before a start time of the image and ends after the start time of the image. A live image is then generated by synchronizing the start time of the image with the journal. This includes evaluating or analyzing the journal relative to the backup to determine or synchronize the start time relative to the entries in the journal.

Abstract: The present disclosure pertains to parsing addresses using a deep learning model. The deep learning model may be trained using a plurality of reference address records and a plurality of modifications to the plurality of reference address records. In some implementations, the model can be a multi-layer bi-directional long short-term memory recurrent neural network model. The output of the model may include indications of an address component type for each character of the address. The output can be parsed based on the indications of the address component type to obtain a plurality of labeled address components for the address. The labeled address components can be compared to reference address records to determine a matched address record identifying a geographic location.

Abstract: A client of a distributed database service may conveniently enable replication of data from a source table to a destination (e.g., a different service/database table) by submitting a request enable replication for the source table. In response to the request to enable replication, the database service enables replication for the source table. To replicate a change, the database service may modify a format of the change based on a data storage format of the destination that is different than a data storage format of the database service. The database service monitors the performance of the replication and based on the performance, the database service may automatically modify the capacity to perform the replication of changes to the destination (e.g., by assigning additional resources to replication).

Abstract: A method and system for maintaining live database data across hybrid storage. Specifically, the disclosed method and system entail accessing live backup database data in part residing on local storage and in part residing on remote storage. That is, on occasion, available local storage capacity may fall short of the required free storage space to accommodate the full restoration or recovery of a given database. Accordingly, to overcome this shortfall, the disclosed method and system detect and cycle the recovery of frequently accessed asset (or database) data files, of the given database, from remote storage onto local storage.

Abstract: A mechanism is provided in a data processing system for hybrid cloud management. The mechanism generates hybrid cloud storage features and hybrid cloud environment factors. The mechanism performs a dynamic confidence method on the hybrid cloud features based on the hybrid cloud environment factors using a deep learning model to generate a hybrid cloud storage profile. The mechanism performing model optimization on the deep learning model and generating a files-storage matrix. The mechanism generates a hybrid cloud file profile based on the hybrid cloud storage profile and the files-storage matrix. The mechanism generates a target file matrix based on the hybrid cloud storage profile and the hybrid cloud file profile. The mechanism stores files based on the target file matrix.

Abstract: Disclosed herein is a data science platform that is built with a specific focus on monitoring and analyzing the operation of industrial assets, such as trucking assets, rail assets, construction assets, mining assets, wind assets, thermal assets, oil-and-gas assets, and manufacturing assets, among other possibilities. The disclosed data science platform is configured to carry out operations including (i) ingesting asset-related data from various different data sources and storing it for downstream use, (ii) transforming the ingested asset-related data into a desired formatting structure and then storing it for downstream use, (iii) evaluating the asset-related data to derive insights about an asset's operation that may be of interest to a platform user, which may involve data science models that have been specifically designed to analyze asset-related data in order to gain a deeper understanding of an asset's operation, and (iv) presenting derived insights and other asset-related data to platform users.

Abstract: A secure joining system is a secure joining system comprising a plurality of secure computation apparatuses; and the plurality of secure computation apparatuses are provided with vector joining parts 11n, first permutation calculating parts 12n, first permutation applying parts 13n, first vector generating parts 14n, second vector generating parts 15n, bit-flipping parts 16n, second permutation calculating parts 17n, second permutation applying parts 18n, third vector generating parts 19n, inverse permutation applying parts 110n, vector separating parts 111n, third permutation applying parts 112n, attribute value permutating parts 113n and fourth vector generating parts 114n.

Abstract: Various embodiments provide methods, apparatus, systems, computing devices, computing entities, and/or the like for identifying targeted data for a data subject across a plurality of data objects in a data source. In accordance with one embodiment, a method is provided comprising: receiving a request to identify targeted data for a data subject; identifying a first data object using metadata for a data source that identifies the first data object as associated with a first targeted data type for a data portion from the request; identifying a first data field from a graph data structure of the first data object that identifies the first data field as used for storing data having the first targeted data type; and querying the first data object based on the first data field and the data for the first targeted data type to identify a first targeted data portion for the data subject.

Abstract: The present disclosure provides for an on-line venue in which search results are displayed with rich media and qualified content and the ability to contact multiple of the sources anonymously or otherwise communicate what product or service they want to purchase by posting an interactive request that a number of sellers can then directly respond to. This enables a higher quality of web search results and for the buyer's to directly match their needs with qualified vendors. A buyer's request can be broadcast to relevant sellers or service providers that can be preselected by the buyer. Such embodiments may take the burden from a buyer in finding the right products and services by self-qualifying the request to proactive prospective sellers.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for maintaining the anonymity of survey respondents while providing useful data to an analyst. In particular, in one or more embodiments, the disclosed systems utilize various anonymity protections based on various anonymity thresholds. For example, the presently disclosed systems and methods may disallow or modify potentially identifying data filters, including generating alternate data groupings. Further, the systems and methods may modify text responses to reduce identification risk.

Abstract: A system and computer-implemented method includes providing first item rating scores for items associated with stored item data. The items are arranged in an initial item taxonomy that includes a first item assigned to a first initial item category. The system receives additional item data associated with the first item and transmits the data to a machine learning (ML) execution tool used to identify an applicable computer model. The system retrieves the item data and processes it using the computer model. The system revises the initial item taxonomy to create a revised item taxonomy including a new item category. The system reassigns the item to the new item category and generates one or more achievement requirements for all of the items. The system determines achievement point values for the achievement requirements for each item and calculates a second item rating score based on the achievement point values.

Abstract: An example system includes a processor to receive concepts extracted from a result set corresponding to a query and result associations for each extracted concept. The processor is to build a graph based on the extracted concepts, wherein the graph comprises a number of nodes representing the extracted concepts and weighted edges representing similarity between concepts extracted from shared results. The processor is to partition the graph into subgraphs with vertices corresponding to candidate facets for vertices having higher sums of weighted edges. The processor is to rank the candidate facets. The processor is to select higher ranked candidate facets to use as facets. The processor is to output facets with a result set in response to the query.

Abstract: Techniques are disclosed relating to data validation using encode values. In various embodiments, a data monitoring system may retrieve a plurality of datasets from a live database at a non-production datacenter. The data monitoring system may perform encoding operations on one or more of the plurality of datasets to generate encode values that correspond to the plurality of datasets. The data monitoring system may then retrieve an updated dataset, for example from an experimental database at the non-production datacenter, and perform validation operations to validate one or more characteristics of the updated dataset. For example, in some embodiments, the data monitoring system may retrieve the encode values corresponding to the plurality of datasets and use the encode values to validate the updated dataset. The data monitoring system may then generate a validation output indicative of a result of the validation operations.

Abstract: A system and method are disclosed for managing snapshots of a file system. In accordance with one implementation, the method includes receiving, by a processing device, a request to access a snapshot of a file system and in response to determining that the requested snapshot is active, providing, to the user account, access to the requested snapshot. The method also includes in response to determining that the requested snapshot is inactive: activating the requested snapshot, providing to the user account, after the activating, access to the requested snapshot; and in response to determining, after the activating, that a number of active snapshots exceeds a threshold number of active snapshots, selecting an active snapshot and deactivating the selected active snapshot, wherein the threshold number of active snapshots corresponds to a limit on resources of the file system that are devoted to active snapshots.

Abstract: Techniques are described herein for simulating triggers in a database. A database server receives a query that targets a database managed by the database server. The database server is registered with a plugin that determines whether the query is a particular type of query. If so, plugin sends a message to an external process that includes features of the query. The database server can also execute the query regardless of whether the particular type of query is detected.

Abstract: Injecting override instructions associated with query executions instructions performed on a distributed database includes receiving a data-query; generating, by a first database instance, a query plan that includes a first query execution instruction for transmission to a second database instance; transmitting, by the first database instance, a request for partial results to the second database instance, where the request includes the first query execution instruction and an indication of override instructions corresponding to the first query execution instruction; responsive to a determination that the request includes the indication, including, by the second database instance, the override instructions in a set of high-level language query instructions; obtaining, by the second database instance, a machine language query based on the set; executing, at the second database instance, the machine language query to obtain the partial results; and transmitting, by the second database instance, the partial resul