Abstract: A method and system for configuring a computer for data classification using ordinal regression includes: receiving and storing a data set having data with a plurality of data features that have an ordinal relationship; generating a plurality of ordinal classification bins based on the relationship of the data features, at least one ordinal classification bin having walls defined by at least two hyperplanes; generating an ordinal regression model of the data set illustrating the data of the data set arranged into the plurality of ordinal classification bins; and tuning the slopes of the walls of the at least one ordinal classification bin based on the relationships between the plurality of data features of the data arranged within the at least one ordinal classification bin such that the slopes of the two hyperplanes defining the walls of the at least one ordinal classification bin are not parallel.

Abstract: Embodiments of the present invention provide a computer system a computer program product, and a method that comprises analyzing identified data for a determined conversion of the identified data, wherein the identified data is input data stored on an external database; automatically converting the analyzed data to a uniform domain by mapping a data route within the analyzed data, predicting a plurality of outcomes based on an application of a plurality of scenarios associated with the mapped data route, ranking the predicted outcomes based on a positive match percentage for the analyzed data, and converting the analyzed data associated with at least one ranked outcome using a relational algebra algorithm; and dynamically transmitting the converted, analyzed data into at least one section of a machine learning data pipeline.

Abstract: A sub-archive is initiated. The sub-archive saves changes that have occurred since a previous final archive. Changes to an operational database (i.e., the operational database that is being archived) are allowed during the first sub-archive. A final archive is initiated in series after the sub-archive has completed. The final archive does not allow changes to the operational database when the final archive is active. In one embodiment, the sub-archive may comprise a plurality of sub-archives that depend on an amount of outstanding changes that exist in the operational database.

Abstract: A method includes accessing, from a data store, at least one predefined data classification for asset data associated with multiple assets in an industrial process control system, wherein the at least one predefined data classification is associated with one or more first policies, wherein the data store stores a plurality of data classifications for asset data. The method also includes receiving user input of a customization to the at least one predefined data classification to generate at least one customized data classification associated with one or more second policies. The method further includes storing the at least one customized data classification in the data store. The method also includes collecting asset data from at least one of the multiple assets. The method further includes processing the collected asset data according to the one or more second policies associated with the at least one customized data classification.

Abstract: A database system operates by facilitating execution of a query, where each of a plurality of sequential operator execution steps includes: determining whether each operator of a plurality of operators of a query operator execution flow is currently executable; generating a plurality of priority values by calculating a priority value for each operator based on whether each operator is determined to be currently executable, and based on a position value of each operator; identifying one operator of with a most favorable priority value; facilitating execution of the one operator on a queued set of data blocks to generate at least one output data block; identifying a next operator serially positioned consecutively after the one operator; and appending the at least one output data block to another queued set of data blocks of the next operator.

Abstract: Disclosed embodiments include a method performed by server computer(s). The method includes receiving a query and defining a query plan based on the received query. The query plan refers to datasets contained in data sources. The method further includes determining that the received query can be accelerated based on an optimized data structure contained in a memory, where the optimized data structure is derived from a dataset referred to in the query plan. The method further includes modifying the query plan to include the optimized data structure, and executing the modified query plan to obtain query results that satisfy the received query by reading the optimized data structure in lieu of reading at least some data from the data sources.

Abstract: Systems and methods for rapid importation of data including temporally tracked object recognition. One of the methods includes receiving datasets each indicating information associated with one or more objects. Information indicating unique identifying information associated with the objects is accessed, and an updated dataset joining information from datasets that is associated with each object is generated. The updated dataset is maintained to include most recent versions of each of the datasets, with one or more datasets being replaced with more recent versions, and with one or more other datasets being propagated to be the most recent versions. Queries received from clients are responded to, with the queries indicating requests for specific information related to objects.

Abstract: Some embodiments provide a non-transitory machine-readable medium that stores a program. The program identifies a first data structure having a first type. The first data structure is configured to store a set of geometries. The program further identifies a second data structure associated with the first data structure. The second data structure is configured to store modifications to the set of geometries. The program also perform a merge operation on the first data structure and the second data structure to form a third data structure.

Abstract: A tiered storage arrangement is contemplated that provides high speed tier 1 storage for rapid access to recalled data, mid-speed tier 2 storage for data that is not frequently recalled and tier 3 storage for archive purposes that may include tape library storage and even cold storage in vaults. Embodiments contemplate a server linked to all tiered storage devices on one end and a host computer on another. Data files can be migrated between the tiered storage systems based on migration policies, such as time elapsed from being filed or last accessed. Also, embodiments contemplate a time bar displayed at the host computer that provides accurate time predictions of data recall including information of the kind of storage on which a target file is stored and the pathway to recall the target file/s locally to the host computer.

Abstract: A database system supporting persistent queries, using an enhanced persistent query service and various data sources. On receiving a request to create a persistent query from a client software application, the persistent query service: creates a query virtual table; parses the persistent query; creates a plurality of intermediate virtual tables; establishes listeners for the query virtual table; creates a plurality of data source virtual tables; causes the plurality of data source virtual tables to retrieve initial data from data sources; and propagates data via intermediate virtual tables to the persistent query virtual table.

Abstract: A computer-implemented method for optimizing a search index of a search service may be provided. The method may comprise storing continuously search queries of the search service, receiving a content item to be indexed, adding the content item temporarily to the a main index of the search service, determining a set of document relevancy factor (DRF) values for the content item for a selected set of stored search queries, determining a combined document relevancy factor value out of the determined set of document relevancy factor values for the content item, comparing the combined document relevancy factor value for the content item to a document relevancy factor threshold value, and adding, in response to the comparing, the content item permanently to an index based on the results of the comparing.

Abstract: An example embodiment may involve obtaining training time series data spanning an observation time window and comprising a series of values of a metric at regularly-spaced sample points in time, and analyzing the training time series data to determine one of a periodicity or a pseudo-periodicity across a plurality of consecutive sub-windows, each equal in size to a reference time period and each spanned by the same number N of sample points of metric values. A reference pattern corresponding to a model time series having no anomalies, as well as a reference threshold, may be determined and stored. Runtime time series data may then be obtained and time aligned with the reference pattern. Deviations between the runtime time series and the reference pattern may be identified as anomalies if they exceed the reference threshold. Identified anomalies may be displayed in a display device.

Abstract: A document retrieval apparatus includes: a storage unit that stores documents and dictionaries applied to a model, a correspondence between a model and documents applied to the model, and a correspondence between a document and dictionaries applied to the dictionary; a model selecting unit that selects a model; a search target document specifying unit that specifies documents applied to the model selected by the model selecting unit as search target documents; a dictionary specifying unit that specifies dictionaries applied to the search target document; a query receiving unit that inputs a query; a search keyword extraction unit that extracts a search keyword group by applying the dictionary specified by the dictionary specifying unit to the query; a retrieving unit that retrieves the search target document using the search keyword group; and a retrieval result presenting unit that displays search results retrieved by the retrieving unit.

Abstract: A backup and restore coordinator configured to receive a plurality of backup and restore requests from at least two uncoordinated backup functionalities implemented in a virtual environment, the virtual environment including a hypervisor hosting a plurality of virtual machines and a backup server. The backup and restore coordinator configured to extract respective information from the plurality of backup and restore requests including target data, backup resource information, and a type of request. The backup and restore coordinator configured to order the plurality of backup and restore requests in a prioritized queue based on the information extracted from the plurality of backup and restore requests.

Abstract: A system and computer implemented method for execution of aggregation expressions on a distributed non-relational database system is provided. The method comprises the acts of determining, by a computer system, an optimization for execution of an aggregation operation, wherein the aggregation operation includes a plurality of data operations on a distributed non-relational database; modifying, by the computer system, the plurality of data operations to optimize execution; splitting the aggregation operation into a distributed aggregation operation and a merged aggregation operation; instructing each of a plurality of shard servers to perform the distributed aggregation operation; aggregating, at a merging shard server, the results of the distributed aggregation operation from each of the plurality of shard servers; and performing the merged aggregation operation on the aggregated results of the distributed aggregation operation from each of the plurality of shard servers.

Abstract: A processor may determine that a particular computer-readable vehicle repair order (RO) (e.g., including first and second RO portions) corresponds to an existing cluster of ROs due to the particular RO including RO data that refers to a particular vehicle symptom. The processor may determine that the first RO portion includes first data representative of a non-specific vehicle component and may then responsively also determine that the second RO portion includes second data that the at least one processor can use to determine a specific vehicle component associated with the particular RO. Responsively, the processor may determine the specific vehicle component based on the first and second data and may then add the particular RO to a different cluster of ROs that is arranged to contain ROs that correspond to the particular vehicle symptom and to the specific vehicle component.

Abstract: Examples of the present disclosure describe systems and methods relating to context rules in a graph or isolated collection. In an example, information in an isolated collection may be associated with one or more contexts. The information may be represented within the isolated collection based on one or more rules, and one or more of the rules may be associated with one or more contexts to which the information relates, thereby indicating a context association. A context association may indicate a positive, negative, or other relationship between one or more rules and one or more contexts. Based on the context association, information within the isolated collection may be adapted to generate different views of the isolated collection for different contexts. As such, relevant, useful, or actionable information may be included or emphasized, while information that is not as relevant, useful, or actionable may be omitted or deemphasized.

Abstract: Systems, methods, and computer-readable media for determining column ordering of a data storage table for search optimization are described herein. In some examples, a computing system is configured to receive input containing statistics of a plurality of queries. The computing system can then determine a new column order (i.e., layout) based at least in part on the statistics. In some example techniques described herein, the computing system can determine the new column order based at least in part on the hardware components storing the data storage table, storage system parameters, and/or user preference information. Example techniques described herein can apply the new column order to data subsequently added to the data storage table. Example techniques described herein can apply the new column order to existing data in the data storage table.

Abstract: A method and apparatus for generating information are disclosed. An implementation of the method includes: receiving a target text, the target text including an objective and descriptive information of the objective; performing a dependency syntax parsing on the target text to generate a dependency tree of the target text; matching predetermined syntactic structure tree with the dependency tree to obtain at least one triple, a triple including a subject, a predicate, and an object; and determining, based on words contained in a triple among the at least one triple and a predetermined weight of the syntactic structure tree matched to obtain the triple, a target triple among the at least one triple.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform: receiving a set of keywords from a graphical user interface of an electronic device of a user; pre-processing at least one keyword of the set of keywords; receiving a hierarchical categorization; pre-processing at least one category of the hierarchical categorization; determining a respective similarity between each of the at least one keyword of the set of keywords and each of the at least one category of the hierarchical categorization; determining a respective confidence level of a most likely category in the hierarchical categorization for each of the at least one keyword of the set of keywords using the respective similarity between each of the at least one keyword of the set of keywords and each of the at least one category of the hierarchical categorization; ranking each of the at least one keyword of the set of k