Abstract: Systems, methods, and non-transitory computer-readable media are disclosed for generating generate explanatory paths for column annotations determined using a knowledge graph and a deep representation learning model. For instance, the disclosed systems can utilize a knowledge graph to generate an explanatory path for a column label determination from a deep representation learning model. For example, the disclosed systems can identify a column and determine a label for the column using a knowledge graph (e.g., a representation of a knowledge graph) that includes encodings of columns, column features, relational edges, and candidate labels. Then, the disclosed systems can determine a set of candidate paths between the column and the determined label for the column within the knowledge graph. Moreover, the disclosed systems can generate an explanatory path by ranking and selecting paths from the set of candidate paths using a greedy ranking and/or diversified ranking approach.

Abstract: Techniques facilitating automatic feature extraction from a relational database are provided. In an embodiment, a method can include generating an entity graph based on a relational database, wherein the entity graph comprises a first node associated with a first table in the relational database and a second node associated with a second table in the relational database. In another embodiment, the method can include joining the first table and the second table based on an edge between the first table and the second table defined by the entity graph, wherein a resulting joined table is connected by a column of data. In another embodiment, the method can include extracting a feature from the column of data using a data mining algorithm selected from a set of data mining algorithms based on a type of data in the column of data.

Abstract: A system comprises a data source storing data, a data processing unit (DPU) comprising an integrated circuit having programmable processor cores and a hardware-based regular expression (RegEx) engine, and a control node configured to generate a data flow graph for configuring the DPUs to execute the analytical operation to be performed on the data. The analytical operation specifies a query having at least one query predicate. A controller is configured to receive the data flow graph and, in response, configures the DPU to input the data as one or more data streams, and configure the RegEx engine to operate according to one or more deterministic finite automata (DFAs) or non-deterministic finite automata (NFAs) to evaluate the query predicate against the data by applying one or more regular expressions to the one or more data streams.

Abstract: Systems and methods are described for customizable data streams in a streaming data processing system. Routing criteria for the customizable data streams are defined by a user, an automated process, or any other process. The routing criteria can be defined using graphical controls. The streaming data processing system uses the routing criteria to determine data that should be used to populate a particular data stream. Further, processing pipelines are customized such that a particular processing pipeline can obtain data from a particular user defined data stream and write data to a particular user defined data stream. Data is routed through the user defined data streams and customized processing pipelines based on a data route. A data route for a set of data may include multiple user defined data streams and multiple processing pipelines. The data route can include a loop of processing pipelines and data streams.

Abstract: Systems and methods for generating augmented search results are disclosed. An example method may be performed by one or more processors of a ranking system and include receiving a search query, generating, for each respective data asset of a plurality of data assets, a query relevancy score indicating a likelihood that the respective data asset is relevant to the search query, retrieving, for each of a number of potentially relevant data assets, a utility score indicating a likelihood that the potentially relevant data asset is useful, generating, for each of the number of potentially relevant data assets, an augmented query score indicating a likelihood that the potentially relevant data asset is relevant to and useful for the search query based on the query relevancy scores and the utility scores, and generating augmented search results for the search query based on the augmented query scores.

Abstract: A method and system for converting non-ordered categorical data stored within a column in a data set into an ordered or continuous data stored in a new column within the data set. Each distinct categorical value in the nominal data column is represented by a corresponding distinct numerical value in the new column. The new representative numerical values are derived by constructing separate time series for each distinct value in the nominal data column and by calculating the similarities between the shapes of the time series. The proximity of the time series is captured in a numeric distance score. Each distinct distance score corresponds to a distinct value in the nominal data column and is a valid representation of that value in machine learning, deep learning, and statistical analysis.

Abstract: A method and an electronic device for providing information associated with work and personal life are provided. An electronic device according to various embodiments may include a user interface, a processor electrically connected to the user interface, and a memory electrically connected to the processor. The memory stores instructions which when executed by the processor cause the processor to determine a first zone and a second zone different from the first zone, based on location information and time information of the electronic device, obtain a first time during which the electronic device is located in the first zone and a second time during which the electronic device is located in the second zone, and display information associated with the first time and the second time on the user interface.

Abstract: Methods, systems, and apparatuses, among other things, may provide for an interactive dynamic mapping engine (iDME) for business intelligence, which may interactively obtain information for user devices from sources and schema unknown to the user devices.

Abstract: Disclosed herein are apparatuses and methods for preserving selections from multiple search queries. An implementation may comprise receiving multiple search queries from a user and storing user selections from each search query result in a temporary database. Contents of the temporary database may be generated for simultaneous display with search query results on a graphical user interface. A user may then select actions to perform in relation to the selections in the temporary database and the system may transmit commands to execute the actions.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for responding to a query. In some implementations, a computer obtains a query. The computer determines a meaning for each term in the query. The computer determines user data for the user that submitted the query. The computer identifies one or more ontologies based on the meanings for at least some of the terms. The computer identifies a knowledge graph based on the identified ontologies and the user data. The computer generates a response to the query by traversing a path of the identified knowledge graph to identify items in the knowledge graph based on the determined meaning for each of the terms. The computer generates path data that represents the path taken by the computer through the identified knowledge graph. The computer provides the generated response and the path data to the client device.

Abstract: Systems and methods are provided for automatically recommending content. One example method includes receiving, from a computing device, a request for content and generating an initial result set in response to the request. A user profile associated with the request is identified. Based on the initial result set and the user profile, a positivity index score for the initial result set is determined. Based on the positivity index score, a type of additional content to add to the initial result set is determined. A modified result set is generated by adding the additional content to the initial result set. At least a portion of the modified result set is transmitted to the computing device.

Abstract: An information output receives a conversational sentence, parameterizes one or more entities included in one or more received conversational sentences, searches a database using the to acquire a search result, and outputs the search result.

Abstract: A device retrieves historical data and new data each a respective hardware component identifier and a respective associated value. The device creates a synthesized set of data by having subsets for anomalous data, data that is associated with an attenuation signal, and other data. The device discards the anomalous data and weights the data associated with an attenuation signal. The device generates a searchable database, the searchable database including each hardware component named by an entry of the synthesized set of data, along with an associated value determined based on the weighted value of the entry. The device receives user input of a search query, and outputs search results based on a comparison of the user input of the search query to entries of the searchable database.

Abstract: Rather than relying on pre-defined scheduling of secondary copy operations such as backup jobs, the illustrative opportunistic approach initiates secondary copy operations based on changing operational conditions in a storage management system. An adaptive backup readiness score is based on a number of backup-readiness operational factors. An illustrative enhanced data agent which is associated with the target database application (or other executable component) may monitor the operational factors and determine the backup readiness score based on weights assigned to the respective operational factors. The enhanced data agent may evaluate recent backup jobs to determine which of the operational factors that contributed to the backup readiness score may have been most relevant.

Abstract: A method and a computer program product are used generating an index of a scoring payload dataset. Correlation coefficients for correlations between input data values and output data values of the machine learning model provided by the scoring payload datasets as well as performance data values of the processes provided by process datasets are calculated. Features of which feature values are used as input data values are ranked according to their importance using the correlation coefficients. For the features of a set of highest-ranking features feature value sets with feature values of the respective features are selected from the scoring payload datasets and a database index of the selected feature value sets is generated.

Abstract: Techniques are disclosed relating to methods that include preprocessing, by a computer system, records of a database to create one or more token sets for a given record. The created token sets may correspond to ones of a plurality of search string functions, and may include token sets that include a plurality of possible substrings located within data strings of a corresponding database record. The methods may further include receiving a query for a search of the database. The query may include at least one of the plurality of search string functions. The method may also include performing the search by traversing, using at least a portion of the records, at least one token set corresponding to the included search string functions, as well as returning results for the search based on the query and the traversing.

Abstract: A network storage volume stores first entries in a first-mode storage bucket and a second entries in a second-mode storage bucket. The first-mode storage bucket has first bucket metadata, and the second-mode storage bucket has second bucket metadata. A computer-implemented method includes comparing a utilized capacity of the network storage volume to a target capacity information of the network storage volume to obtain a comparison result. Based on the comparison result, at least one bucket is selected to be purged from the buckets of the network storage volume based at least in part on bucket metadata of the buckets. The method further includes causing a purge of the at least one selected bucket from the network storage volume.

Abstract: Examples disclosed herein relate to a method comprising detecting a plurality of changes in a database, wherein the database is used to configure a switch operating traffic on a network. The method may include determining that a subset of the plurality of changes are to be deferred before being used to configure the switch, wherein each change in the subset has a potential dependency with at least one other change in the subset. The method may also include iterating through each change in the subset. The iteration may include confirming that a target change has a dependency with another change in the subset, resolving the dependency and transmitting the target change to an object manager for configuration of the switch.

Abstract: A computer-implemented method provides application-based query transformations. The method includes determining an application is initiated. The method includes identifying a set of execution units included in the application. The execution units are based on of a set of queries in the application and a set of actions in the application. The method also includes building a query dependency graph (QDG) comprising a plurality of nodes, wherein each node of the plurality of nodes is correlated to an execution unit, and each node is linked to at least one additional node, the link indicating a relative execution order and a common attribute each node and the additional node. The method includes merging, based on a performance architecture, two or more of the set of execution units into a section. The method includes processing the application according to the QDG.

Abstract: A system, computer-readable storage medium storing at least one program, and a computer-implemented method for identifying availability of media items is presented. A search query is received from a client device of a user. Instances of media items that satisfy the search query and that are available on content sources accessible to the client device of the user are identified. Aggregate information for the media items is determined based on the instances of the media items. The aggregate information for the media items is transmitted to the client device.