Abstract: A device for coupling a machine, in particular a machine tool, having a number N of data sources for providing data of the machine in data source-specific file formats having a plurality of applications is provided. The device includes a transformation unit, which is designed to transform data of one of the N data sources present in one of the data source-specific data formats to data of a generic semantic data model for at least one of the applications and data of one of the applications present in the generic semantic data model to data of one of the data source-specific data formats for one of the N data sources. The transformation unit thus advantageously establishes data interoperability between the respective application and the respective data source of the machine. Also provided is a method and to a computer program product for coupling a machine to a plurality of applications.

Abstract: A system for data processing using machine learning processing and distributed architecture is described. Specifically, proprietary data transformation rules to be applied for the data processing may be stored at edge computing devices, while the bulk of data processing may be performed at a central computing node that houses the databases. A subset of a data set, in the database, may be sent from the central computing node to the edge computing node. The edge computing node may generate a second data set based on applying data transformation rules to the subset of the data set. The central computing node may determine, using a machine learning (ML) algorithm and based on the subset of the data set and the second data set, the data transformation rules, which may then be applied to the rest of the data set.

Abstract: Method, computer program product, and computer system are provided. Traffic is collected against a NoSQL database by an activity collector. A database transaction log is periodically extracted and analyzed. The collected traffic and the analyzed database transaction log are input to building a knowledge base of database access patterns. Current traffic is captured and used to compute an activity threshold. Traffic is directed to a workload processor based on the activity threshold. Traffic is directed to an intensive insert/update/delete (IUD) processor in response to the activity threshold exceeding a configured threshold. A plurality of temporary shards is generated along with an adaptive key and adaptive index in the plurality of temporary shards. The intensive IUD processor traffic is re-directed to the plurality of temporary shards while the activity threshold exceeds the configured threshold.

Abstract: A virtual machine disk image file backup is selected among a plurality of virtual machine disk image file backups stored on a backup storage based on a backup update policy. A version of the selected virtual machine disk image file backup is mounted. Based on the backup update policy, an update to the mounted version of the selected virtual machine disk image file backup is applied without restoring the selected virtual machine disk image file backup. The updated version of the selected virtual machine disk image file backup is stored on the backup storage.

Abstract: Described herein is a technique to facilitate filtering during candidate retrieval stage performed by an information retrieval system that utilizes embedding models. An aNN indexing structure is created for each end-user, and in some instances, each activity type. This allows a single request for candidate content items to invoke a single process to obtain content items that satisfy the filtering criteria (e.g., in this case, the in-network requirement) from the separate per-end-user indexes.

Abstract: The present disclosed is directed to systems, methods, and devices for obtaining feedback information from individuals to reveal group preferences and to systems, methods, and devices for enabling providers to provide outcomes which utilize, at least in part, the preferences of the group. For example, a system comprising a plurality of devices, wherein at least one device of the plurality of devices captures at least one feedback in one substantially simple transaction; and the at least one device of the plurality of devices sends the at least one captured feedback to at least one computer; and the at least one computer receives the least one feedback; and the at least one feedback can be given at one or more of the following: periodic time intervals, predefined time intervals, random time intervals, substantially random time intervals and substantially any time.

Abstract: A network-accessible toolbox permits collaborative annotation, facilitating interaction and communication among users. In an implementation, content on a Web page, or other page or document accessible through a network or the Internet, can be annotated. A user can view the page and with the toolbox, select content on the page and make an annotation or suggestion. Multiple users can view and make annotations to the same page at the same time. After annotations are made, users can view the page with annotations made by other users. The author or owner of the page can accept or reject the annotations or suggestions made to the page. If the owner accepts a particular suggestion, the selected content is replaced with the suggestion.

Abstract: A computer implemented method performs data skipping in a hierarchically organized computing system. A group of processor units determines leaf node data sketches for data in leaf nodes in the hierarchically organized computing system. The leaf node data sketches summarize attributes of data in the leaf nodes. The group of processor units aggregates the leaf node data sketches at intermediate nodes in the hierarchically organized computing system to form aggregated data sketches at the intermediate nodes and retains data sketches received at the intermediate nodes from a group of child nodes to form retained data sketches. The retained data sketches are one of leaf node data sketches and the aggregated data sketches. The group of processor units searches the data using the retained data sketches and the data skipping within the hierarchically organized computing system in response to queries made to the intermediate nodes in the hierarchically organized computing system.

Abstract: Disclosed are embodiments for sorting rows of a dataset after a JOIN operation. In one embodiment, a method is disclosed comprising performing a JOIN operation on an annotation dataset, the performing of the JOIN operation generating an unordered dataset; grouping a plurality of rows in the unordered dataset into a plurality of buckets, the grouping performed based on a root dataset associated with the annotation dataset; sorting each bucket, the sorting comprising sorting each bucket independently; and combining each sorted bucket into a sorted dataset.

Abstract: Examples disclosed herein relate to propagating changes made on a file system volume of a primary cluster of nodes to the same file system volume also being managed by a secondary cluster of nodes. An application is executed on both clusters, and data changes on the primary cluster are mirrored to the secondary cluster using an exo-clone file. The exo-clone file includes the differences between two or more snapshots of the volume on the primary cluster, along with identifiers of the change blocks and (optionally) state information thereof. Just these changes, identifiers, and state information are packaged in the exo-clone file and then exported to the secondary cluster, which in turn makes the changes to its version of the volume. Exporting just the changes to the data blocks and the corresponding block identifiers drastically reduces the information needed to be exchanged and processed to keep the two volumes consistent.

Abstract: Methods, systems, and computer readable mediums for performing a free-form query are disclosed. According to one exemplary embodiment, a method for performing a free-form query includes receiving free-form information for requesting information about a computing system, converting the free-form information into at least one compatible query for querying at least one data set, querying, using the at least one compatible query, the at least one data set for the information about the computing system, and providing the information about the computing system.

Abstract: In an example embodiment, a request is received, via a graphical user interface, to add a new object to a directory of objects, the new object having a first category in a hierarchical taxonomy of categories and objects. Then one or more questions previously assigned to the first category and/or one or more existing objects within the first category are retrieved. Each of the retrieved one or more questions and information about the new object are then fed into a first machine learned model trained to output a probability that a question is applicable to an object. One or more questions are generated for the new object based on the probability for each of the retrieved one or more questions. At least one of the one or more generated questions is then assigned to the new object.

Abstract: Methods for enhancing compatibility of a document of an entity with an organization's database on a computer server to facilitate detection of a fraudulent submission. Methods may include receiving a populated document in a first format from the entity, using a processor to digitize the document into a digital format, such as bytes, and further into a second format, where the first format may not be compatible with the database and the second format may be compatible with the database. Methods may include using the processor, optionally running a statistical model, to determine an entity identifier, a predicted value of a data field in the document, and whether there is a difference between the value in the predicted data field and a corresponding value in the populated document. Methods may include implementing a corrective action, such as raising a fraud alert at the organization, when there is a difference.

Abstract: In an example embodiment, a differentially private function is computed via secure computation. Secure computation allows multiple parties to compute a function without learning details about the data. The differentially private function is performed via probability distribution, which then permits computation of a result that is likely to be very close to the actual value without being so exact that it can be used to deduce the underlying data itself.

Abstract: A system for indexing, updating, and search haplotypes for genetic genealogical discovery in genotype databases. The system includes a pool of genetic indexes, a haplotype ingestion engine, and a haplotype query engine. The haplotypes of a number of individuals in a genotype database are indexed by a pool of multiple panels, and each panel pool can be dynamically updated by the insertion or deletion of individual haplotypes. A genetic genealogical search of a query haplotype against the database is achieved by first projecting the query onto a subset of panels in the pool, then conducting long match queries over each panel, and finally aggregating the identified long matches into Identical-by-Descent segments, i.e., DNA matches, between the query and the haplotypes in the database.

Abstract: Disclosed herein are system, method, and computer program product embodiments for classifying data objects using machine learning. In an embodiment, an artificial neural network may be trained to identify explained variable values corresponding to data object attributes. For example, the explained variables may be a category and a subcategory with the subcategory having a hierarchical relationship to the category. The artificial neural network may then receive a data record having one or more attribute values. The neural network may then identify a first and second explained variable value corresponding to the one or more attribute values based on the trained neural network model. The first and second explained variable values may then be associated with the data record. For example, if the data record is stored in a database, the record may be updated to include the first and second explained variable values.

Abstract: A system that enables development and execution of predictive models comprises a centralized data management system, a data extraction tool a model validation tool and a model execution tool. In embodiments, a data management system includes a data management server that can be accessed via a web browser that stores data in the form of a flat file. An extraction tool extracts data. A model validation tool validates a model by scoring an analytical environment data set and a production environment data set. A model execution tool allows a user to select when and how often a model is scored.

Abstract: A system for providing a directory service for generating web presence pages made available on a network may include a computer processor and memory having instructions stored thereon. The instructions may instruct the computer processor to parse registration information of a registrant domain name to obtain keywords and to search the network using the keywords for information about the registrant. Registrant information may be created based on information obtained, and a trusted web presence page may be generated. The trusted web presence page may include at least a first portion of the registrant information as read only content. A link may be created between a profile page and the trusted web presence page. The profile page may include at least a customizable second portion of the registrant information. The trusted web presence page may be published on the network.

Abstract: Methods, systems, and computer-readable storage media for selective use of Internet-of-Things (IoT) data in data analytics systems. Implementations include receiving IoT data from an IoT device, determining that hardening is to be applied to the IoT data, comparing a timestamp of the IoT data to a hardening value, and in response to comparing, selectively using the IoT data in one or more uses by the data analytics system.

Abstract: Methods and systems for file level prioritization during a data restore operation are disclosed. According to some embodiments, in response to a restore request to restore one or more files and for each file, the method includes retrieving file information and a critical value associated with the file, and calculating a Euclidean distance of the file to a consecutive file based on the critical value. The method further includes sorting the file(s) based on the calculated Euclidean distance of each file. The method further includes restoring the sorted file(s) at a target site.