Abstract: In various embodiments, a natural language (NL) application implements functionality that enables users to more effectively access various data storage systems based on NL requests. As described, the operations of the NL application are guided by, at least in part, on one or more templates and/or machine-learning models. Advantageously, the templates and/or machine-learning models provide a flexible framework that may be readily tailored to reduce the amount of time and user effort associated with processing NL requests and to increase the overall accuracy of NL application implementations.

Abstract: A unified data store and transaction system queries an n-tuple-based multimodal data structure via a mutable tuple-based interface the mutable tuple-based interface, the interface including a memory controller, and a query operation set. The system receives a tuple from a mutable tuple-based query interface with a tuple-reader and reading the tuple into a tuple object, and evaluates the tuple object against semantic rules via a tuple evaluator.

Abstract: Systems and methods are provided for improved interactive graphical user interfaces. The system allows users to visually construct queries of a database. The system can dynamically generate visual representations of supplemental data and cumulative data. Users can share annotations related to user input queries via the graphical user interface.

Abstract: A method includes generating a table in a relational database, the table comprising an empty column reserved for a custom tag. The column has a default column name. The method also includes, in response to an instruction to create the custom tag, generating a column mapping that maps a name of the custom tag to the column name. The column mapping is stored outside the relational database and is used by a parser to translate between the name of the custom tag and the column name.

Abstract: Systems and methods for data quality monitoring are provided. Various embodiments include a data monitoring system that integrates into a data pipeline. The data monitoring system may receive a call from the data pipeline to analyze data inputs entering the data pipeline. The monitoring system can generate metadata describing the data inputs and compare the generated metadata with previously generated metadata to determine if the data inputs are historically consistent. The data monitoring system may return a consistency measure to the data pipeline. In further embodiments, the data monitoring system can generate metadata describing data outputs from the data pipeline and compare the output metadata to previously generated output metadata. In further embodiments, the data monitoring system may operate as a read only entity in a database. The monitoring system may monitor for changes in the database and determine when adverse changes occur in the database.

Abstract: Herein is a self-tuning database management system (DBMS) storing JavaScript object notation (JSON) documents and operating a JSON datatype as native to the DBMS. In an embodiment, a computer hosts a DBMS that executes a data definition language (DDL) statement that defines, in a database dictionary of the DBMS, a JSON document column of a database table that stores JSON documents as instances of the JSON datatype that is native in the DBMS. The DBMS may autonomously set or adjust configuration settings that control behaviors such as a default width of a JSON document column, in lining or not of the JSON document column, kind and scope and duration of indexing of the JSON document column, and/or caching of the JSON document column such as in an in memory columnar unit (IMCU). The DBMS may use the various configuration settings to control how JSON documents and the native JSON datatype are stored and/or processed.

Abstract: Recovery of a database system by taking the database system offline is initiated. Thereafter, recovery operations specified by a redo log of the database system are replayed. A cleanup log is generated that identifies cleanup operations occurring during the replay of the recovery operations for garbage collection. Concurrent with the startup of the database, garbage collection of the cleanup operations as specified in the database savepoint is initiated. In addition, concurrent with the replay of the recovery operations, garbage collection of the cleanup operations specified by the cleanup log is initiated. The database system is later brought online after all of the recovery operations are replayed.

Abstract: Systems and methods for contextual memory capture and recall are provided. The contextual memory capture and recall systems and methods help a user create, store, and recall memory information associated with an identified activity. The contextual memory capture and recall systems and methods are capable of identifying user activities where a memory inquiry may be desirable, creating a memory inquiry with a recommended memory action based on the activity, providing the memory inquiry to the user, and automatically linking an accepted memory action, along with any received memory information for the memory action, with the identified activity.

Abstract: A method is provided for analyzing a classification in a machine learning model (ML). In the method, the ML model is trained using a training dataset to produce a trained ML model. One or more samples are provided to the trained ML model to produce one or more prediction classifications. A gradient is determined for the one of more samples at a predetermined layer of the trained ML model. The one or more gradients and the one or more prediction classifications for each sample are stored. Also, an intermediate value of the ML model may be stored. Then, a sample is chosen to analyze. A gradient of the sample is determined if the gradient was not already determined when the at least one gradient is determined. Using the at least one gradient, and one or more of a data structure, a predetermined metric, and an intermediate value, the k nearest neighbors to the sample are determined. A report comprising the sample and the k nearest neighbors may be provided for analysis.

Abstract: A method for tracking user interactions with an application includes: storing the application in a memory of a mobile device, the application being associated with an instrumented widget and a library, the widget including an event logger; executing the application and the widget; receiving, through a user interface of the mobile device, an input corresponding to the event logger of the widget; logging, by the library, the input corresponding to the event logger of the widget in the memory of the mobile device; filtering a plurality of events, including the input corresponding to the event logger of the widget, to manage what data is reported to a monitor; and transmitting the input corresponding to the event logger of the widget to a server as monitored data.

Abstract: Techniques are disclosed for handling database queries from multiple different application versions using a single database. A computer system executing a database management system (DBMS) may receive a database query for a database, where the database query is received from a particular version of an application having a plurality of versions. The database query may specify the particular version. The computer system may then identify catalog tables, where the catalog tables include version information columns storing version access information. The computer system may determine that version access information for the database query indicates that one or more database objects corresponding to the database query are accessible to the particular version of the application.

Abstract: A method of providing automated help includes receiving, at a computer system including at least one processor and at least one computer readable medium storing machine-executable instructions, user inputs for utilizing a plurality of functions of a computer program, detecting, at the computer system, a plurality of user actions utilizing the plurality of functions, as a function of the user inputs, at the computer system, an action trigger indicating a user help condition, wherein detecting further comprises identifying, in a help trigger database associating a plurality of action triggers with user help conditions, an action trigger matching at least a user action of the plurality of user actions, by the computer system, a first area of expertise associated with the user help condition, based on the identified first area of expertise associated with the user help condition, identifying, by the computer system, expertise to provide assistance to the user.

Abstract: Provided are a data storage method, a storage device, a server and a storage medium, the method includes: obtaining, by a server, image data of different dimensions (S11); according to the association identity carried by each of the image data, determining, by the server, the image data of the different dimensions with the same association identity as association data (S12); sending the image data of the different dimensions included in the association data to target data tables of databases with different dimensions for storage, respectively (S13), wherein, the databases of different dimensions are located in the same storage apparatus, regarding the target data tables of the database of different dimensions, the table name prefixes of the target data tables are different, but the table name suffixes are the same. This method can store image data in association, meanwhile, when performing associated query, the loss of associated data can be avoided.

Abstract: The disclosure provides examples of methods, apparatuses, systems, and computer program products for implementing a search indexer. One example method includes receiving, by index workflow circuitry, a search index update indicator, causing, by the index workflow circuitry and in response to receiving the search index update indicator, index generation circuitry to retrieve data sets from a plurality of data sources, calculating a checksum for each of the data sets, comparing the checksum for each of the data sets to a set of search index metadata, in response to determining that at least one checksum for at least one of the data sets does not match a metadata checksum from the set of search index metadata, generating a set of search index data from the data set corresponding to the at least one checksum, generating a search index using at least the set of search index data, and transmitting the search index to a search service for use in responding to at least one search query.

Abstract: Disclosed are a method and system for selecting target data. The method of selecting target data may include steps of grouping data included in a database into objects each being a minimum process processing unit based on dependency between tables within the database, setting a selection criterion for target data based on at least one field of the data included in the database, and extracting target data corresponding to the set selection criterion by taking into consideration dependency between tables included in the object.

Abstract: Disclosed is a social networking system which provides personal pages for users and enables other users to modify the personal page of a given user. Generally, a given webpage is enabled to be collaboratively modified and edited by multiple users. In some embodiments, the owner of the personal page approves the trusted users and may define one or more rules that automatically define a trusted user. In some embodiments, rules for modifying/editing a social webpage may specify the type of operations users can perform on the page and may specify one or more potential target actions.

Abstract: In one embodiment, a method includes generating, for each of a plurality of first entities of an online social network, a plurality of candidate keywords associated with the first entity by extracting a plurality of n-grams from a plurality of content objects associated with the first entity. The method also includes identifying, from the plurality of first entities, responsive to determining that a second entity of the online social network is interacting with a search interface of the online social network, a plurality of entities associated with the second entity based at least in part on a search history of the second entity. The method also includes sending, to a client system of the second entity, for each of the plurality of identified entities associated with the second entity, instructions for presenting one or more suggested queries comprising one or more of the generated candidate keywords associated with the identified entity.

Abstract: Servicing database requests using canonicalized tables including maintaining a canonical table repository of canonicalized tables, wherein each canonicalized table is a transformed version of a table previously retrieved from a database; receiving, from a client computing system, a request for a table from the database; generating a description of a canonical version of the requested table; determining whether the canonical version of the requested table matches a canonicalized table in the canonical table repository; and if the canonical version of the requested table matches the canonicalized table in the canonical table repository: transforming the matching canonicalized table based on the received request for the table; and providing, to the client computing system, the transformed matching canonicalized table.

Abstract: In entity transition from legacy systems to a big data distributed data platform, numerous system-based architectural gaps have surfaced. There exists a need for a bridge component for each of the architectural gaps in order to support the entity transition to the big data distributed data platform. These bridge components include a variety of frameworks that are configured to automate certain processes that are needed for the transition. These processes have only become necessary as a result of the Hadoop platform. The automated processes include a snapshot load platform. The snapshot load platform enables the addition of a new view to the historical tables. The platform includes replacing the entire table in a truncated scenario. The platform includes replacing cases in a refresh or update scenario.

Abstract: System and method for migration of a legacy datastore include converting legacy datastore information from the legacy datastore to a target database system information. The target database system information belongs to a target database management system. A legacy datastore call is mapped to a data manipulation language (DML) statement. The legacy datastore call requests the legacy datastore information. Scripting language for the target database management system is generated using the DML statement.