Abstract: This application relates to features for a mobile device that allow the mobile device to assign utility values to applications and thereafter suggest applications for a user to execute. The suggested application can be derived from a list of applications that have been assigned a utility by software in the mobile device. The utility assignment of the individual applications from the list of applications can be performed based on the occurrence of an event, an environmental change, or a period of frequent application usage. A feedback mechanism is provided in some embodiments for more accurately assigning a utility to particular applications. The feedback mechanism can track what a user does during a period of suggestion for certain applications and thereafter modify the utility of applications based on what applications a user selects during the period of suggestion.

Abstract: In some embodiments, there is provided triggering a chat bot session to make a change to a master data entity at a master data store; determining an identity of the master data entity and the master data store associated with the chat bot session by at least extracting context information from an application and/or a user interface; generating, based on the identity of the master data entity and the master data store, a change command to make the change to the master data entity; and sending a change request including the change command to make the change to the master data entity at the master data store. Related systems, methods, and articles of manufacture are also disclosed.

Abstract: A stored multi-part object management method, system, and computer program product for managing a stored multi-part object in a data storage application that includes modifying a stored multi-part object based on executing a predetermined operation and reporting a change to the multi-part object as a result of the modifying based on receiving a status request for the multi-part object.

Abstract: Various embodiments can implement a multi-system or node architecture that can be deployed on-demand and augment existing systems with pre-configured nodes that can be installed within existing architecture. The multi-node architecture is flexible for integration into many systems and can also stand alone to provide data validation and assurance. Various embodiments of the multi-node architecture enable private and public distributed ledgers (e.g., blockchains) that enhance security, enhance confidentiality, and eliminate the need to trust the provider/hosts of the data validation information and/or the hosts of the confidential information.

Abstract: A computer system for performing cloud-based enhanced rules conflict checking is provided. The computer system is programmed to store a plurality of rules for transmitting to a plurality of destination systems and receive a data message for transmission to the plurality of destination systems from a first requesting system. The computer system is programmed to compare the data message to a first set of rules to validate the data message and if the data message is validated for the first set of rules, instruct the first requesting system to transmit the data message to the plurality of destination systems. The computer system is further programmed to receive the data message for transmission to one or more remaining destination systems from a second requesting system and compare the data message to a second set of rules for validating the data message.

Abstract: The disclosure herein describes causing a database operation to be performed via a microservice. A translation layer exposes a translation API that is configured to receive commands in an API command format. A command in the API command format is received from a command sender that includes a database type. A microservice configured to perform the received command based on the included database type is identified. The command is transferred to the identified microservice, which is configured to translate the transferred command to a database command format associated with the database type and perform the translated command in association with a database. A response is received from the microservice based on performance of the command by the microservice, wherein the received response is in a response format that is compatible with the exposed translation API, and the received response is provided, via the exposed translation API, to the command sender.

Abstract: In some embodiments, there is provided a method including receiving a first package for processing as part of a job; unpacking the first package to include additional data linked to the first package, wherein the first package including the additional data forms a first unpacked package; in response to the first unpacked package being less than a package threshold size, processing the first unpacked package to form a first output; and in response to the first unpacked data being more than the package threshold size, rescaling the first package to satisfy the package threshold size before additional unpacking and processing is performed on the first package. Related manufactured articles, devices, systems, and methods are also disclosed.

Abstract: Embodiments of the present disclosure may provide a data sharing system implemented as a local application of a distributed database. A query from a query template can be validated and executed against shared dataset that comprises portions of data from the database dataset and additional portions of data from another database of the distributed database.

Abstract: The disclosure is directed to systems and techniques for executing a documentation application displaying a graphical user interface having a content-creation field configured to receive textual input. A link-creation window may be generated, which facilitates browsing content without leaving a current application. Using the disclosed interface, a user can generate a selectable graphical object that links to other content, the selectable graphical object created from within the context of the content-creation field interface.

Abstract: A system with graph-based Natural Language Processing (NLP) for querying, analyzing, and visualizing complex data structures is described. Such a system executes a generalized AI language model; defines and migrates a training dataset into a graph database by exposing data sources to an executing AI language model that self-defines a structure and self-writes an executable script to query the original data sources and self-writes code to load the extracted data into a graph database in the form of new nodes and new relationships with directionality between the nodes. The system further includes means for loading the extracted data into the graph database; condensing the information stored within the graph database into a condensed data structure representing the full architecture of the data in a natural language format; and responding to human language inquiries with responsive text, speech, and visualizations using the data loaded into the graph database.

Abstract: A computer-implemented method is disclosed. The method includes: receiving a request for retrieval of data satisfying one or more criteria, the request including at least one data request parameter; searching a database storing example queries based on the request to identify at least one matching query; providing, to a large language model (LLM), an input prompt to generate a query purporting to retrieve data satisfying the one or more criteria, the input prompt including the at least one data request parameter and the at least one matching query as an example; and receiving, from the LLM, a result including the generated query.

Abstract: Techniques are described herein for forecasting datasets using blend of temporal aggregation and grouped aggregation. An example method can include a device accessing a first and second time series, comprising a first data point associated with a first time step and a first value and a second data point associated with a second time step and a second value. The method can further include the device determining a grouped aggregated data point using the first and second time series by aligning the first and second data point. The method can further include the device determining the grouped aggregated data point by summing the first and second value. The method can further include determining a grouped aggregated time series. The method can further include the device determining a first set of input values for a machine learning model. The method can further include the device determining a first forecasted future value.

Abstract: A system that enables searching for representing listings for accommodation reservations on a map is described. The system receives, by a network site of a listing network platform, input comprising search criteria associated with a geographical region and identifies a plurality of listings matching the search criteria. The system identifies a first subset listings of the plurality of listings that is each associated with a respective location that is within a boundary associated with the geographical region and a second subset listings of the plurality of listings that is each associated with a respective location that is outside the boundary associated with the geographical region. The system visually distinguishes the first subset of listings from the second subset of listings on a map-based graphical user interface (GUI) that represents the plurality of listings matching the search criteria.

Abstract: Aspects of the disclosure are directed to methods, systems, and non-transitory computer readable media for automatically generating queries on a database from natural language text using in-context learning to leverage zero-shot and few-shot adaptation capabilities of large language models (LLMs). The methods, systems, and non-transitory computer readable media can consider database information, employ execution based consistency decoding, and employ a mixture of prompts and/or LLMs.

Abstract: Methods, systems, and computer program products for managing interactions between a content management system (CMS) and a large language model (LLM) system. The semantics of user questions can be considered before prompting an LLM, or alternatively, before querying datasets that are local to the CMS. Given a user question to be answered, the embedding of the user question can be matched against preconfigured sample question embeddings to determine a best match. A prompt corresponding to the determined best match is then configured based on identification of the class or classes that correspond to the matched question. Prompts for provision to LLMs can be synthesized based on a particular user's identity and/or based on the particular user's historical collaboration activities over objects of the CMS. The LLM can be hosted by a third-party provider. Alternatively all or portions of a large language model system can be hosted within the CMS.

Abstract: Techniques for converting natural language queries into query language syntax are disclosed. In some embodiments, a natural language query is processed using an artificial intelligence based framework, and an output query specified in a prescribed query language is generated by converting or translating the processed natural language query into the prescribed query language using the artificial intelligence based framework.

Abstract: A cluster computing system maintains a first set of queues for short queries and a set second set for longer queries. The first set is allocated a majority of the cluster's processing resources and processes queries on a first in first out basis. The second set is allocated a minority of the cluster's processing resources which are shared among queries in the second set. Accordingly, the system assigns each query to the first set of queues for a fixed amount of resource time. While a query is processing, the system monitors the query's resource time and reassigns the query to the second set of queues if the query has not completed within the allotted amount of resource time. Thus, short queries receive the necessary resources to complete quickly without getting stuck behind longer queries while ensuring that longer queries continue to make progress.

Abstract: A data search apparatus includes a plurality of storage modules configured to store a data table. Any one of the plurality of storage modules stores a part of entries of the data table. Any entry in the data table is unique in the plurality of storage modules, and storage addresses of entries stored in at least one of the plurality of storage modules are inconsecutive.

Abstract: A database system is operable to read a plurality of rows from memory of a relational database stored in memory resources. Each of the plurality of rows are assigned to a corresponding one of a plurality of training data subsets of the plurality of rows based on performing a row dispersal process. A plurality of sets of candidate model coefficients are generated based on executing a plurality of parallelized optimization processes. Each set of candidate model coefficients is generated based on executing a corresponding parallelized optimization process upon a corresponding training data subset independently from executing other ones of the plurality of parallelized optimization processes upon other ones of the plurality of training data subsets. A most favorable set of candidate model coefficients is selected from the plurality of sets of candidate model coefficients generated via the plurality of parallelized optimization processes.

Abstract: Techniques for querying a storage system involve receiving a query request for querying a resource in the storage system, determining a query type of the query request according to configuration information, generating a corresponding query statement according to the query type, and querying the resource from the storage system through the query statement. Accordingly, a query result can be obtained by generating a query statement (or referred to as “query expression”) corresponding to a query request to query the corresponding database directly, thereby improving the query efficiency in making queries to the storage system and enhancing the user experience. Such techniques can be easily integrated into any product having query needs (e.g. a storage system product), thus improving the product development efficiency and the ease of use and maintainability of the product.

Abstract: A database system operates by: determining a set of assigned segments based on data ownership information; generating a plurality of segment handles and a corresponding plurality of segment metadata for the set of assigned segments based on performing a segment activation step for the set of assigned segments; determining a first query for execution requiring access to a first segment of the set of assigned segments; and executing an IO operator of the first query based on loading the first segment by utilizing a corresponding one of the plurality of segment handles.

Abstract: Method and apparatus for optimized data partition selection for related queries. A query to be executed over a plurality of data records is received. The plurality of data records comprises a first set of data records stored in a first database distributed across a plurality of partitions and a second set of data records stored in a second database. An input vector is generated based on the query, the first and second databases. The input vector is processed using a machine learning (ML) model to predict a cost for executing the query if one or more data records in the second set of data records are loaded to a first partition of the first database. A plan is selected for loading the one or more data records from the second set of data records to the first partition based on the predicted cost for executing the query.

Abstract: Systems, apparatuses, methods, and computer program products are provided. For example, a computer-implemented method may include receiving one or more datasets from a user. In some embodiments, computer-implemented method may include storing at least a portion of the one or more datasets in a first shard during a first time period. In some embodiments, the first shard comprises shard data. In some embodiments, the shard data is associated with a data size. In some embodiments, computer-implemented method may include determining that the data size of the shard data in the first shard is greater than a first data size threshold. In some embodiments, computer-implemented method may include in response to the determination that the data size of the shard data in the first shard is greater than the first data size threshold, transferring at least a portion of the shard data in the first shard to a second shard.

Abstract: The subject technology receives a query, the query including a statement for performing the query. The subject technology performs a first lookup operation on a multi-phase cache based on the query. The subject technology performs, in response to a first cache miss of the multi-phase cache, parsing of the statement from the query. The subject technology performs, based on the parsing, a compilation process on the query to generate a compiled query plan, the compilation process determining an optimization and a generalization for the query. The subject technology determines that the compiled query plan is cacheable. The subject technology registers, in response to the compiled query plan being cacheable, a dummy entry in the multi-phase cache.

Abstract: A database system is operable to execute a first to generate the machine learning model from a training set of rows based on accessing and processing the training set of rows via a plurality of operators. system configuration data tracking a plurality of objects of a database system is updated to further track the machine learning model as a corresponding first object tracked via the system configuration data. A query output for a second query indicating applying of the machine learning model via execution of the second query based on applying the machine learning model to a set of rows in accordance with at least one property of the corresponding first object based on accessing the system configuration data.

Abstract: A method for efficiently supporting deletion in a probabilistic data structure, and related computing or storage system are described. A processor, computing system or storage system constructs a table and a summary table for determining whether there is an entry for a value in the table. The summary table has buckets pointed to by address fields of values. Each bucket has a prefix table, a transit table, signature table and a first indicator. The system tracks deletion and addition of items of the table and summary table through the first indicators.

Abstract: A database-based data shard processing method and apparatus, a medium, and an electronic device are provided. The method includes: obtaining a processing request for a shard to be processed that corresponds to a first boundary and a second boundary; determining a first type of logical condition, which includes first sub-conditions for defining data greater than or equal to the first boundary, based on the first boundary, and determining a second type of logical condition, which includes second sub-conditions for defining data less than the second boundary, based on the second boundary; combining the first sub-conditions with the second sub-conditions separately to obtain candidate combined conditions; determining executable structured query languages based on an execution statement corresponding to the processing request and the candidate combined conditions; and executing the structured query languages to obtain a processing result corresponding to the processing request.

Abstract: A method for execution by at least one computing entity of a database system, the method includes obtaining a plurality of data partitions of a data set for storage in the database system, where the data set is organized in rows and columns, and the rows correspond to data records and the columns correspond to fields of the data records. The method further includes dividing a first partition of a plurality of data partitions to produce a first number of first raw data segments for storage in the database system, where the first number is based on a first data storage coding scheme. The method further includes dividing a second partition of the plurality of data partitions to produce a second number of second raw data segments for storage in the database system, where the second number is based on a second data storage coding scheme.

Abstract: A non-transitory computer-readable recording medium stores an information processing program for causing a computer to execute processing including: generating, from first data in which values of a plurality of attributes included in each sample are accumulated for each sample, second data obtained by binarizing, for each sample, the values of the plurality of attributes included in each sample based on an attribute condition set in advance; enumerating, by using the second data, sets of attribute conditions in which all sample sets indicate true values; computing, for each set of attribute conditions, a correlation between the plurality of attributes in the first data in a sample set associated with each set of attribute conditions; and selecting a set of attribute conditions determined to have a correlation as a condition to be causally searched.

Abstract: A database system is operable to receive a plurality of records of a dataset for storage. A plurality of segment row data is generated from the plurality of records and a plurality of parity data corresponding to the plurality of segment row data is generated. The plurality of segment row data is stored via a first storage mechanism. The plurality of parity data is stored via a second storage mechanism. Execution of a plurality of queries against the dataset is facilitated by accessing the plurality of segment row data via the first storage mechanism. A storage failure of one of the plurality of segment row data via the first storage mechanism is detected. The one of the plurality of segment row data is recovered for storage via the first storage mechanism based on accessing at least one parity data via the second storage mechanism.

Abstract: An non-transitory computer readable medium is described herein related to enhancing an SAP Archive Information System running on a SAP NetWeaver Application Server. The enhancements enable the SAP Archive Information System to query a remote relational database for archived business data. The enhancements offers multiple alternative ways of interfacing with such a database and of merging the query results obtained from such database into the SAP-standard output structures of the SAP Archive Information System.

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: Embodiments of the present disclosure may provide a data clean room architecture that dynamically restricts data included in the clean room. The data clean room architecture can implement row access policy or dynamic data masking for row and column based restrictions of data provided through the clean room. The data clean room architecture can provide a limited set of data that does not require obfuscation of data for direction matching and correlation of data in the different datasets, such as matching user identifiers or emails.

Abstract: Provided are systems and methods for generating a resultant dynamic dataset are provided. The method comprises receiving a first data stream of a first data layer associated with locations included as part of an external environment, receiving a second data stream of a second data layer, generating a first dynamic dataset from the first data stream as corresponding to the locations and a second dynamic dataset from the second data stream as corresponding to the locations, generating an output corresponding to a resultant dynamic dataset that is based on the first dynamic dataset and the second dynamic dataset, the generating of the output including associating at least one value from the first dynamic dataset and at least one value from the second dynamic dataset with at least one of the locations, and providing the output corresponding to the resultant dynamic dataset, the providing including displaying, storing, processing, and/or transmitting.

Abstract: Disclosed are various approaches performing distributed profiling and validation. A query is generated for profile data for data stored in a data warehouse. Then, the query for the profile data is sent to the data warehouse. The profile data is then received from the data warehouse. Later, in response to a request to load the data stored in the data warehouse into a table in a data store, a determination is made as to whether the data stored in the data warehouse complies with a validation rule.

Abstract: An apparatus and method for generating an instruction set for a user is provided. The apparatus includes at least a processor and a memory connected to the processor. The memory contains instructions configuring the at least a processor to receive a client datum from a client, where the client datum describes resources of the client, and to receive a user datum from the user, where user datum includes a target datum that describes resource transfer data from the client to the user. Initiation of resource transfer described by the target datum is triggered by the pattern exceeding a threshold. In addition, the memory contains instructions configuring the at least a processor to generate an interface query data structure including an input field and to display the first transfer datum and the second transfer datum hierarchically based on a user-input datum input to the input field.

Abstract: Technologies described herein relate to dense retrieval and ranking of search results. A query indicating a computing context or user input is received. An embedding of the query is computed by way of a first encoder, and candidate results selected from a pool of potential results based upon the embedding of the query and embeddings of the potential results. A similarity score for a first of the candidate results is computed by way of a second encoder trained based upon an order metric that defines a ranking over a training set of potential results. The first encoder is trained based upon output of the second encoder prior to computing the embedding of the query. The candidate results are ranked based upon the similarity score of the first candidate result, and results responsive to the query are identified based upon the ranking. The identified results are output to a computing device.

Abstract: Data regarding a subject is received over a communication network. The data is parsed to extract data elements that are associated with various aspects of the subject. A plurality of sub-scores is calculated based on the values associated with the data elements. A combined score is calculated based on the plurality of sub-scores and weights corresponding to the plurality of sub-scores. An indication of the combined score associated with the subject is output.

Abstract: Various embodiments are provided herein for systems and methods for real-time, or near real-time, multi-dimensional ranking of experts. In at least one embodiment, receiving one or more evaluation datasets; for each given evaluation dataset, associating the evaluation dataset with: (i) at least one evaluation data category, (ii) at least one taxonomy category, and (iii) at least one expert of the plurality of experts; subsequently, receiving one or more search filter criteria for ranking at least a subset of the plurality of experts; generating a ranking of the at least subset of the plurality of experts, wherein the ranking is based on the search filter criteria, and is further generated based on the associations determined for each evaluation dataset; and displaying, on a user interface, at least a portion of the plurality of rankings as the multi-dimensional ranking of the plurality of experts.

Abstract: A method and system, performed in a server computing device, of identifying and allocating sentiment attributions.

Abstract: A user device includes a processing unit that executes a search application. Executing the search application causes the processing unit to receive a user search query, send the user search query to a plurality of target applications, and receive a set of search results from each of the target applications. Each search result includes application state access data configured to access an application state of the target application associated with the search result. Executing the search application causes the processing unit to rank the search results, display the ranked search results, and detect user selection of one of the displayed search results. Additionally, executing the search application causes the processing unit to send the application state access data associated with the selected search result to the target application associated with the selected search result and display the application state accessed using the application state access data.

Abstract: A real-time technique for identifying truth-telling data in a data stream includes determining, based on a situational map of the data stream, an expected range of values for incoming data points associated with a trend in the data stream. The technique further includes receiving, in the incoming data points, a data point that is outside the expected range of values. The data point that is outside the expected range of values is stored for an analysis of the trend after receiving more of the incoming data points. The analysis of the trend is executed using the data point that is outside the expected range of values for the analysis to indicate whether the trend in the data stream has changed.

Abstract: A computing device receives a natural language input specifying a first search term and a second search term, directed to a dataset. The device (i) executes, for the first search term, first queries against a search index to retrieve a first set of labeled trend events; and (ii) executes for the second search term, second queries against the search index to retrieve a second set of labeled trend events. Each labeled trend event has a respective chart identifier. The device constructs sequences of labeled trend events based on the retrieved sets of labeled trend events, assigns each sequence into groups according to the respective chart identifier, and ranks the groups. The device retrieves data corresponding to a subset of line charts having the respective chart identifiers of the ranked groups, generates the subset of line charts, and displays one or more line charts of the subset.

Abstract: Provided are a method and apparatus for proposing a solution, based on a survey. The method includes storing indicators in a data format in a database, wherein each of the indicators is transformed from a pattern of responses of respondents related to an issue, transforming a response of a user to the survey to a patterned response, the patterned response in the data format, selecting an indicator to be compared with the patterned response among the indicators, the indicators and the patterned response are being in the same data format, determining one or more issues, based on a comparison of the patterned response and the selected indicator, determining a proposal solution set, based on the one or more issues, and displaying the one or more issues and the proposal solution set on a device of the user.

Abstract: This specification provides a multi-party database including a central node and a plurality of databases. The central node has a disclosed first interface. Each of a plurality of query engines corresponding to the plurality of databases includes a second interface configured to interact with the first interface. The central node can determine a plurality of target databases related to a query request from the plurality of databases based on the query request; and send a query indication to a plurality of target query engines corresponding to the plurality of target databases through the first interface. The plurality of target query engines can receive the query indication from second interfaces in the plurality of target query engines, and execute the query indication to obtain a query result; and send the query result to the first interface in the central node through the second interfaces.

Abstract: Functionality in a network device is specified by an application installation file that describes programmable devices used to implement the functionality. Profiles for programmable devices generated from the application installation file and stored on the network device. A profile database stores profiles associated with functionality specified in previously received application installation files. A profile associated with a selected functionality is selected to implement the selected functionality, including loading one or more bitfiles identified in the selected profile to program the programmable devices associated with the selected functionality.

Abstract: Creating data warehouse views for input tables including: selecting, by a workbook manager, a subset of columns of an input table stored in a cloud-based data warehouse, wherein the subset of columns excludes one or more metadata columns of the input table; generating, by the workbook manager, a view of the input table based on the subset of columns; and storing, by the workbook manager, the view of the input table in the cloud-based data warehouse.

Abstract: Systems and methods are provided for generating extract-transform-load (“ETL”) machine learning (“ML”) pipeline validation rules based on user-input, wherein the ETL ML pipeline validation rules may be applicable to validate an ETL ML pipeline against multiple test datasets. The ETL ML pipeline validation rules may comprise compute-type validation rules for computing expected values of data structures within a dataset output by the ETL ML pipeline. The ETL ML pipeline validation rules may comprise check-type validation rules for checking whether data structures within a dataset output by the ETL ML pipeline have intended characteristics.

Abstract: A computing platform configurable to allow users to graphically represent relationships between database records may be provided to a plurality of organizations. A request to generate a customizable visualization for graphically representing relationships between a root database record and child database records in a customizable format may be processed. Graphical representations of the root database record and the child database records may be caused to be displayed in accordance with the customizable format.

Abstract: A computing device receives a natural language input specifying search terms directed to a dataset. The device parses the input into tokens and executes queries against a search index to retrieve a plurality of labeled trend events. Each labeled trend event has a respective chart identifier. The device determines a respective composite score for each labeled trend event and individually assigns each labeled trend event to a respective group. For each group, the device sorts the respective labeled trend events within the respective group according to respective composite scores, determines a respective final score for each group, and ranks the groups according to one or more determined final scores. The device retrieves data corresponding to a first subset of line charts having the respective chart identifiers of the ranked groups, generates the first subset of line charts, and displays one or more line charts of the first subset with annotation.