Abstract: A retrieval method including outputting a first retrieval result to a result area, the first retrieval result being obtained by referring to a first database based on a first retrieval query entered into a retrieval area, outputting a second retrieval result and the first retrieval result in the result area, the second retrieval result being obtained by referring the first database based on a second retrieval query in response to acquiring a delimiter character and the second retrieval query entered next to the first retrieval query in the retrieval area.

Abstract: Methods, systems, and apparatuses for providing access to records of a database stored on a database server in a cloud database platform are described herein. A data sharing platform may determine a shared view definition for access to the database. The data sharing platform may determine rules that specify criteria that limit access to the records stored by the database. The one or more first rules may be received via a user interface. The data sharing platform may perform, based on the rules, a data access certification process on the records stored by the database to generate a table of certification results. The data sharing platform may generate, based on the table of certification results, and without modifying the records stored by the database, a limited consumer view definition. Based on updates to the records, a new limited consumer view definition may be generated.

Abstract: A data processing method is provided for an electronic device. The method includes obtaining from a target node a transaction request for off-chain data, parsing the transaction request to obtain a transaction parameter and a chain height parameter of the target node, querying, according to the chain height parameter of the target node, for the off-chain data, in response to determining the off-chain data is present in the data manager, sending the off-chain data to the target node, and in response to determining the off-chain data is absent in the data manager, obtaining the off-chain data from a data source according to a type of the target node.

Abstract: Some embodiments provide a method for migrating data from a first database to a second database. The data is susceptible to change at the first database before all of the data is migrated to the second database and is available for access through the second database. The method transfers segments of data incrementally from the first database to the second database and generates a first digital signature for each transferred segment. The method identifies a set of transferred segments that have been modified in the first database before the data is available for access through the second database by generating a second digital signature for each transferred segment in the set and comparing the second digital signature for the segments with the first digital signature for the segments. The method transfers the modified segments from the first database to the second database in order to replace the previously transferred segments.

Abstract: A system and method permit users to selectively search for, and identify short segments (called snippets) of music. The user may enter one or more search terms for which they are searching within a database of musical selections. Once the search terms have been defined, the user initiates the search by selecting the search button. The system searches for one or more of the musical selections that most closely match the user's search parameters, and returns those musical selections as search results back to the user. The user then selects one of the results of the search that they like best. Once the selection is made, the user may input recipient information for the person to which they would like to send this musical selection. This musical selection may then be sent to the recipient by the system.

Abstract: Technologies are described for routing structured query language (SQL) statements to elastic compute nodes (ECNs) using workload classes within a distributed database environment. The elastic compute nodes do not store persistent database tables. For example, a SQL statement can be received for execution within the distributed database environment. A workload class can be identified that matches properties of the SQL statement. Based on the workload class, a routing location hint can be obtained that identifies a set of elastic compute nodes. The SQL statement can then be routed to one of the identified elastic compute nodes for execution. Execution of the SQL statement at the elastic compute node can involve retrieving database data from other nodes which store persistent database tables.

Abstract: Computer-implemented methods and systems for migrating business data from source business system to target business system are described. The method performed by server system includes receiving request from user device to migrate source data from source business system to target business system and accessing source metadata associated with source business system and target metadata associated with target business system. The method includes generating one or more source staging tables based on source metadata. The one or more source staging tables include information of a plurality of source columns that is to be mapped. The method includes creating mapping sets for mapping source data to the target metadata, transforming the source data stored in the one or more source staging tables into a target data structure based on the target metadata, and loading a target staging table associated with target business system based, at least in part, on the transforming step.

Abstract: Structure data is received from a database. The structured data may comprise data values and specifying relationships among the data values. A method is provided to include receiving selections of operations to be performed on the structured data and an order of the operations. The operations may include at least one permutation operation. The method may include determining a graphically displayable data format based on the selections of operations. The method may include representing the structured data and the relationships among the data values in the graphically displayable data format. The method may comprise performing operations according to the selections, including, permuting entries of the graphically displayable data format. The permuting may comprise bringing the entries of the graphically displayable data format into a logical order while maintaining the relationships. The method may also include displaying the entries for analysis after performing the operations.

Abstract: Methods and systems are provided for clustering data for use in training models to predict a loss metric for insurance. The historical data is cleaned and aggregated to a quarterly time granularity and a zip code geographic granularity, and features on which to generate the clusters are selected. Clusters are generated using one or more clustering algorithms, evaluated, and the best set of clusters is selected. Clusters may be grouped together based on cluster characteristics. Each cluster or group of clusters is used to train a development model and a forecast model for the loss metric. The accuracy of the development and forecast models is evaluated, and the clustering process is repeated until the accuracy and stability of the development and forecast models is sufficient. At each iteration, historical data may be removed and/or hyperparameters of the clustering algorithms may be adjusted.

Abstract: Methods and systems are provided for predicting and forecasting loss metrics for insurance. One or more models are created to generate development curves to predict ultimate losses for aggregations of long-tail losses, such as bodily injury claim payouts based on the first few months of payout data and other relevant variables. The relevant variables include internal data about policyholders and claims, and external data. Historical data, including potential influential variables and a target, are used to train a predictive development model. The variables are pre-processed and aggregated to an accident-month granularity, then feature reduction techniques are applied to determine the variables that exert the most influence on the target. Dimensionality reduction techniques are then applied to the remaining variables. The most influential variables and the variables created by dimension reduction are used as the input features to train the development model.

Abstract: A data warehouse storing databases for a plurality of users, including service providers hosting data for other users of the data warehouse may implement a data exchange. The data warehouse to verify identity of users and execute instructions with respect to databases of the data warehouse.

Abstract: System, method, and various embodiments for providing a metadata converter and memory management system are described herein. An embodiment operates by determining that first metadata corresponding to a table of a database comprising load preferences for a column level for a plurality of columns of the table, wherein the load preferences include either column load or page load. It is determined that the database is enabled with both load preferences for a table level and load preferences partition level, in addition to load preferences for the column level. Values for the load preferences are automatically assigned for both the table level and the partition level in second metadata, and wherein the second metadata preserves the load preferences for the column level of the first metadata. A query against the table based on load preferences from the second metadata.

Abstract: A system or method for identifying a plurality of entities in a first dataset that satisfy a predetermined target attribute by deploying on the first dataset a relationship model generated from a second dataset having a plurality of entities not in the first dataset.

Abstract: One or more computing devices, systems, and/or methods are provided. A first plurality of sets of device information associated with a plurality of devices may be received and/or identified. The plurality of devices may be grouped into a plurality of groups based upon the first plurality of sets of device information. A plurality of group profiles associated with the plurality of groups may be generated. A first group profile of the plurality of group profiles may be associated with a first group of the plurality of groups. The first group profile may be generated based upon sets of device information, of the first plurality of sets of device information, associated with the first group. A request for content associated with a first device belonging to the first group may be received. A first content item may be selected for presentation via the first device based upon the first group profile.

Abstract: In order to provide filtering of content to be presented on a mobile device, a gesture-based preferencing system and method may be employed. When content is presented to a user, the user may indicate a positive or negative preference toward that content by making a gesture. The gesture may be detected by a motion sensor and the preference of the content indicated by the gesture may be stored in a preference datastore. The preference may be used to subsequently filter content that is to be presented to the user.

Abstract: Systems and methods are provided for generating training data from queries and user interactions associated with media collections related to the queries, and training a machine learning model using the generated training data to generate a trained machine learning model. The systems and methods further provide for receiving a prediction request comprising a query for relevant media collections, analyzing the query to determine query features, determining a plurality of media collections for the query, analyzing the plurality of media collections to determine media collection features for each media collection of the plurality of media collections, and generating, using the trained machine learning model, a semantic matching score for each media collection of the plurality of media collections based on matching the query features to the media collection features for each media collection of the plurality of media collections.

Abstract: The system manages database structure updates. The system may receive, via a development gateway, a development script. The system may also copy, via a backup engine to an update module, an existing object code. The system may deploy, via an update engine, the development script directly to the database structure. The system may also generate new object code within the database structure associated with the existing object code. The system may determine, via a database health monitoring module, at least one of a successful deployment of the new object code or an unsuccessful deployment of the new object code.

Abstract: According to an embodiment of the present invention, a probability to achieve a purpose is increased in a case where information is intermittently allocated to a plurality of elements. An information processing apparatus according to an embodiment of the present invention is an information processing apparatus that allocates information to respective elements included in a first set and includes an allocator. The allocator uses a first subset and a second subset, and allocates the information to at least one element included in the first subset. The first subset is constituted by elements which are included in the first set and in which information allocation may be performed at a present time. The second subset is constituted by elements which are included in the first set and in which the information allocation is not performed at the present time.

Abstract: A system may retrieve a pattern from a pattern database with the pattern identifying a type of sensitive data. The system may also retrieve data identified by a variable from a big data management system. The system may then match the data to the pattern to detect the type of sensitive data in the data. An output may be generated in response to the data matching the pattern. A variable access permission may be retrieved for the variable from a permissions repository, a sensitive data permission may be retrieved for the type of sensitive data from the permissions repository, and the variable access permission may be compared to the sensitive data permission to detect a discrepancy.

Abstract: A data warehouse storing databases for a plurality of users, including service providers hosting data for other users of the data warehouse may implement a data exchange. The data warehouse to verify identity of users and execute instructions with respect to databases of the data warehouse.