Abstract: Implementations are provided for providing responsive audio recordings to user queries that are prerecorded by human beings, rather than generated automatically using speech synthesis processing. In various implementations, a query provided by a user at an input component of a computing device may be used to search a corpus of voice recordings From the searching, a plurality of candidate responsive voice recordings may be identified and ranked based on measures of credibility associated with speakers that created the candidate responsive voice recordings. Based on the ranking, one or more of the plurality of candidate responsive voice recordings may be provided for presentation to the user at an output component of the same computing device or a different computing device.

Abstract: A system for determining whether an entity is potentially violating regulator)/requirements using a machine learning model. The system includes a repository having a plurality of databases that store data and information in a format accessible to users, and a back-end server operatively coupled to the repository and being responsive to the data and information from all of the databases. The back-end server includes a processor for processing the data and information, a communications interface communicatively coupled to the processor, and a memory device storing data and executable code. The code causes the processor to collect data and information from the databases, store the collected data and information in the memory device, process the stored data and information through the machine learning model to determine whether the entity is potentially violating regulatory requirements, and transmit a communication on the interface identifying that the entity is potentially violating regulatory requirements.

Abstract: Methods, apparatuses and systems directed to pattern identification and pattern recognition. In some particular implementations, the invention provides a flexible pattern recognition platform including pattern recognition engines that can be dynamically adjusted to implement specific pattern recognition configurations for individual pattern recognition applications. In some implementations, the present invention also provides for a partition configuration where knowledge elements can be grouped and pattern recognition operations can be individually configured and arranged to allow for multi-level pattern recognition schemes.

Abstract: The system creates a central UUID index mapping multiple local identifiers of multiple records in multiple databases to an identifier unique across the multiple databases including a first database without a UUID index. The first database includes a record having a first identifier. A second database includes an equivalent record having a second identifier different from the first identifier. The universally unique identifier in the central UUID index represents the first and the second identifier. The system receives a request from the first database to obtain an equivalent record from the second database, where the request includes an identifier of a record in the first database. The system determines that the identifier is a local identifier unique to the first database, based on the central UUID index. The system then converts the local identifier to the universally unique identifier, and sends the universally unique identifier to the first database.

Abstract: Computer-implemented methods, systems and products for analytics and discovery of patterns or signals. The method includes a set of operations or steps, including collecting data from a plurality of data sources, the data having a plurality of associated data types, and filtering the collected data based on identifying viable data sources from which the data is collected. The method further includes prioritizing discovery objectives based on analyzing the filtering results, and enriching the filtered collected data from viable data sources according to the prioritized discovery objectives. The method further includes extracting one or more signals from the enriched data using one or more machine learning mechanisms in combination with qualified subject matter expertise input, and graphically displaying the extracted signals in a meaningful way to a human operator such that the human operator is enabled to understand importance of extracted signals.

Abstract: Systems and methods are provided for adaptive data replication. A first data object is stored. One or more first network characteristics of a communication network are detected. A first replication mode is triggered (e.g., a single-master replication mode) based on the one or more first network characteristics of the communication network. The single-master replication may be configured to facilitate real-time synchronizations (e.g., for critical updates). One or more second network characteristics of the communication network are detected. A second replication mode (e.g., a multi-master replication mode) is triggered based on the one or more second network characteristics. The second replication may be configured to facilitate a delayed synchronization (e.g., for non-critical updates) of the first data object and the second data object using the second update file.

Abstract: Methods, apparatuses and systems directed to pattern identification and pattern recognition. In some particular implementations, the invention provides a flexible pattern recognition platform including pattern recognition engines that can be dynamically adjusted to implement specific pattern recognition configurations for individual pattern recognition applications. In some implementations, the present invention also provides for a partition configuration where knowledge elements can be grouped and pattern recognition operations can be individually configured and arranged to allow for multi-level pattern recognition schemes.

Abstract: Methods, apparatuses and systems directed to pattern identification and pattern recognition. In some particular implementations, the invention provides a flexible pattern recognition platform including pattern recognition engines that can be dynamically adjusted to implement specific pattern recognition configurations for individual pattern recognition applications. In some implementations, the present invention also provides for a partition configuration where knowledge elements can be grouped and pattern recognition operations can be individually configured and arranged to allow for multi-level pattern recognition schemes.

Abstract: As described herein, a system, method, and computer program are provided for context-based data-driven classification. Input to be processed using a classifier is identified. Data is obtained from one or more third party data sources, based on the input to be processed. The input is processed, using the classifier, to generate output that includes at least one classification for the input. Both the data from the one or more third party data sources and the output of the classifier are processed to determine a final classification for the input.

Abstract: The described technology is generally directed towards data movement from data storage clusters. A data movement job can be split into data movement tasks, and the data movement tasks can be distributed among multiple nodes of a data storage cluster. In order to distribute the tasks, a data store that identifies the tasks can be split into multiple segments, and different groups of nodes can be assigned affinities to process tasks identified in the different segments. Furthermore, the nodes of each group of nodes can be assigned different start positions within their storage segment, to reduce the likelihood of contention between nodes in connection with claiming a same task. Some of the tasks can be generated in an already claimed state, which also reduces contention and allows for more efficient operation.

Abstract: A non-transitory computer-readable storage medium storing a transmission support program that causes at least one computer to execute a process, the process includes generating a management identifier of a message in response to reception of the message; returning the management identifier to a transmitter of the message; when receiving the management identifier and lists of personal identifiers of individuals who have attributes according to conditions regarding the attributes, from each of a plurality of companies that holds information on the attributes of the individuals, based on reception of the conditions and the management identifier from the transmitter, specifying the personal identifiers that are duplicate between the lists that have the management identifier that is common; and transmitting the specified personal identifiers and the received message.

Abstract: A data consistency analyzer identifies data inconsistencies proactively, providing insights into the financial, business, and technical impact to enable users to make decisions regarding resolution of the inconsistencies. The data consistency analyzer may provide additional insights such as criticality of inconsistencies. Data inconsistencies may be caused by configuration changes to master data. As described herein, data consistency is improved by keeping a constant watch on various master data changes which is one of the major sources towards causing inconsistency and taking necessary actions based on further assessments. Using master data change as initial lead, the inconsistencies would be identified that are not mere database or technical inconsistencies. Along with the primary option of inconsistency check based on master data change, additional options to scan the system based on overall run and run per selection, or application level specific checks will be provided.

Abstract: An apparatus is disclosed. The apparatus may be implemented in a database node or a storage node and includes one or more processors and memory storing instructions for causing the processor to perform a number of operations. Responsive to a page write request, the apparatus determines an identifier corresponding to the requested page, sends component blocks corresponding to the page to a storage node for appending to an append-only storage log of the storage node, receives the physical location of the stored component blocks, and associates the physical storage location of the stored component blocks with the logical identifier corresponding to the page.

Abstract: A synchronization adapter is coupled to the application that does not support synchronization and generates the necessary synchronization metadata for all data in the application that is to be synchronized. The synchronization adapter then combines the metadata to the actual data to be synchronized to form a synchronization feed. The synchronization feed is stored in an internal cache (or data store) which is internal to the application, or an external cache (or data store), which is external to the application, or it can be stored in both caches. The synchronization adapter also intermittently determines whether the application data has changed, thus warranting a change in its metadata, or whether a synchronization operation is warranted to synchronization operation is warranted to synchronize the data with data in another application. In either case, the synchronization adapter makes the changes to the data, or performs a synchronization operation.

Abstract: An illustrative media agent (MA) in a data storage management system instructs a NAS file server (filer) to restore an MA-created synthesized-copy instead of larger filer-created backup copies. The synthesized-copy is designed only for the particular files to be restored and mimics, and is typically much smaller than, a filer-created backup copy. The synthesized-copy is fed to the filer on restore as a “restore data image.” When receiving a restore request for certain backed-up data files, the MA synthesizes the synthesized-copy on the fly. The MA generates a header mimicking a filer-created backup header; extracts files from filer-created backup copies arranging them within the synthesized-copy as if in filer-created backups; and instructs filer to perform a full-volume restore from the synthesized-copy. The MA serves the synthesized-copy piecemeal as available, rather than waiting to synthesize the entire synthesized-copy. The synthesized-copy is not stored at the MA.

Abstract: A method includes receiving, an operation from a container to synchronize container data from memory to a file system mounted by the container and determining whether the file system indicates that the operation is to be ignored. The method further includes, in response to determining that the file system indicates that the operation is to be ignored, preventing, by the operating system kernel executing on the processing device, performance of the operation.

Abstract: Methods, apparatus, and processor-readable storage media for automated database operation classification using artificial intelligence techniques are provided herein. An example computer-implemented method includes obtaining at least one query related to one or more database operations; obtaining information pertaining to a set of multiple storage resources; classifying the at least one query as associated with at least one of multiple subsets of storage resources among the set of multiple storage resources by processing at least a portion of the query and at least a portion of the information pertaining to the set of multiple storage resources using one or more artificial intelligence techniques; and performing one or more automated actions based at least in part on the classifying of the at least one query.

Abstract: Disclosed herein are system, method, and apparatus for generating labels for k-means clusters. The method includes accessing a plurality of data records from a database repository, and storing the plurality of data records into at least one of primary or secondary memory associated with at least one computer processor performing the method, along with a cluster number for each data record. All data records having a same cluster number form a cluster, and each record has been categorized or designated a cluster number out of a total K number of clusters. The method includes for each of a plurality of classification features, performing cluster-based analysis for a first cluster with respect to a single feature to generate a single feature overlap score. The method includes sorting, grouping, and generating a naming label for the first cluster based on the predetermined number of features having the lowest overlap scores.

Abstract: A system for creating and/or maintaining a database is disclosed. In one example, the system includes one or more processors; a classification module configured to determine primary weights for primary data streams, each primary weight referring to a correlation between one of the primary data streams and one segment category of several predefined segment categories; a recognition module configured to identify explicit concepts and implicit concepts in the primary data streams, and to determine first secondary weights characterizing embeddings of the identified concepts; an expansion module configured to determine for the identified concepts respective related concepts; and a storage module configured to save the identified concepts.

Abstract: Improved intelligent personal assistant (IPA) software agents are disclosed that are configured to interact with various people, service providers, files, and/or smart devices. More particularly, this disclosure relates to an improved Natural Language Processing (NLP) Intent Determination Service (IDS) that is able to determine the likely best action to take in response to generic user commands and queries. The improved NLP IDS disclosed is said to be ‘search-based’ because, rather than attempt to parse incoming user commands and queries up front, the incoming user commands and queries are searched against a pre-generated database of exemplary user commands (e.g., having associated action or parsing identifiers) to determine the most relevant search result(s). The associated system actions and known grammar/parsing rules of the most relevant search result(s) may then be used to process the incoming user command or query—without having to actually parse the incoming user command or query from scratch.