Abstract: An information processing device sets: a first argument of a first table join instruction to a second table join instruction as the first argument of the second table join instruction; a second argument of the first table join instruction to the first table join instruction as the first argument of the first table join instruction; a first output data table generated by the first intermediate table generation instruction to the first table join instruction as the second argument of the first table join instruction; and a second output data table generated by the first table join instruction after changing the first and second arguments of the first table join instruction to the second table join instruction as the second argument of the second table join instruction.

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: The present disclosure relates to systems, non-transitory computer-readable media, and methods for synchronizing timestamps associated with media files across a variety of capture devices. For example, the disclosed systems receive a media file captured with a user device and determine, from metadata, initial timestamp information for the media file that includes inaccurate or incomplete time zone information. The disclosed systems determine a predicted time zone for the media file by extracting GPS information from the metadata associated with the media file or identifying a peer media file and utilizing a time zone or GPS information associated with the peer media file. The disclosed systems generate a synchronized timestamp for the media file with updated timestamp information based on the predicted time zone.

Abstract: Described herein is an apparatus and method for training a machine learning model. An apparatus may include a computing device configured to receive a corpus of data containing entries corresponding to a plurality of subjects; identify a plurality of entries within the corpus, corresponding to a first subject of the plurality of subjects and representing medical history of the first subject; determine a plurality of temporal attributes of the plurality of entries; generate a plurality of tokens as a function of the plurality of entries; generate a chronological data structure segment ordering one or more of the plurality of entries and the plurality of tokens, as a function of the plurality of temporal attributes; and train a multimodal machine learning model on a training dataset including the chronological data structure segment.

Abstract: A computing platform may be configured to (i) obtain an input dataset, (ii) construct a graph from the input dataset, (iii) for a given node within the constructed graph, generate a first type of embedding vector using a first embedding technique (e.g., a shallow embedding technique) and a second type of embedding vector using a second embedding technique that differs from the first embedding technique (e.g., a deep embedding technique), and (iv) use the first and second types of embedding vectors for the given node and a data science model to render a given prediction for the given node.

Abstract: The present invention relates to a method for constructing a database schema model by a user by means of a computer, comprising the steps of: providing a set of collections and/or optionally one or more relationships linking at least two of said set of collections; editing one or more of said set of collections, each of which associated with a schema definition displayed by a single table on an entity relationship diagram on a graphical interface on said computer and comprising at least one object and/or one field, said schema definition editable via a tree diagram on said graphical user interface on said computer; automatically generating by means of said computer said database schema model for a database system or a REST API; characterized in that, said set of collections comprises at least one collection comprising a nested object editable via said tree diagram with two levels or more.

Abstract: A system performs efficient startup of executors of a distributed computing engine used for processing queries, for example, database queries. The system starts an executor node and processes a set of queries using the executor node to warm up the executor node. The system performs a checkpoint of the warmed-up executor node to create an image. The image is restored in the target executor nodes. The system may store a checkpoint image for each configuration of an executor node. The configuration is determined based on various factors including the hardware of the executor node, memory allocation of the processes, and so on. The user or restore based on checkpoint images improves efficiency of execution of the startup of executor nodes.

Abstract: Some embodiments provide a program that receives a first selection of a first set of attributes in a first data model, a second selection of a second set of attribute in a second data model, a third selection of a first dimension in the first data model, and a fourth selection of a second dimension in second data model. The program further receives a request for data for a visualization. The program also generates a blend definition based on the first set of attributes, the second set of attributes, the first dimension in the first data model, and the second dimension in the second data model. The program further generates a blended query model based on the blend definition. The program also executes a query based on the blended query model to generate a result set of data. The program provides a visualization that includes the result set of data.

Abstract: Embodiments of the present disclosure provide a method, apparatus, device and storage medium for data processing. If a kernel module sends a data calling request to a userspace process, first modification time information and second modification time information of data corresponding to the data calling request are obtained by the userspace process. The first and second modification time information are used to indicate modification time information of the data in the kernel module and in a file service end, respectively. The first and second modification time information are compared by the userspace process. If the first and second modification time information are inconsistent, a verification invalidation result is returned to the kernel module. The data in the kernel module is invalidated by the kernel module according to the verification invalidation result. The data in the file service is synchronized by the userspace process to the kernel module.

Abstract: A method and system for providing a video query are disclosed. The method includes acquiring context information, training a first machine learning (ML) model using historical data of the software life cycle tool, and removing, by the first ML model, noise from the context information for generating a query including at least one keyword. Once the query is generated, executing, by a second ML model, the query to retrieve at least one video segment from a learning repository. Scoring and ranking is then performed on the at least one video segment. The ranked video segment is then transmitted, to the user interface of the software life cycle tool, and displayed in an ad-hoc manner.

Abstract: Devices, methods and systems for processing database queries formatted differently than the database storage model being queried are disclosed. Processing database queries independent of the storage model of the queried database may be performed by receiving a query for one or more data items stored in a database, determining whether to use at least one query operator that uses data having a format different from the storage model format of at least one of one or more data items stored in the database and converting the format of the data used by the at least one query operator to a format that matches the storage model format of at least one of one or more data items stored in the database. Related systems, methods, and articles of manufacture are also described.

Abstract: An event deduplication system may efficiently perform event deduplication (identifying “new” or “unique” events that might be an anomaly) by using a first stage that has multiple first stage processes running in parallel (e.g., at different data centers) and a single second stage that has a second stage process that receives and processes events from the different first stage processes. The second stage process updates a global state (e.g., lookup table) and periodically publishes the global state to the first stage processes to update their local state. When the second stage process receives a possible new event from a first stage process, it may more accurately determine whether the event is actually a new event based on the global state.

Abstract: Operations of a search management system are disclosed. The operations may include: identifying a data corpus containing a plurality of documents, generating sets of feature vectors representing the plurality of documents, receiving a query to search the data corpus, generating a query vector for the query, identifying a target feature vector that meets a similarity threshold by comparing the query vector to the feature vectors, and presenting a query result that includes at least part of the document. The feature vectors may be generated by executing a multi-step partitioning process for partitioning a respective document into a plurality of document partitions, such that the sets of feature vectors that are generated correspond to the plurality of document partitions for the respective document. The query result may include a target partition from among the plurality of document partitions represented by the target feature vector.

Abstract: The present disclosure relates to computer-implemented methods, software, and systems for controlling the execution of concurrent threads executing tasks in a database management system. A first task is executed at a first thread from a pool of threads for execution of tasks at the database management system. It can be identified that the execution of the first task is paused and that the first task is in a sleep mode. In response to identifying that the first task is in an awake mode after the sleep mode, it can be determined whether a current number of threads in the pool that are currently processing tasks in parallel is below an allowed number of threads. It can be determined that the allowed number of threads has been reached and a waiting status can be assigned to the first task at the first thread.

Abstract: Methods, systems, and devices for data management are described. In some systems, a client may request for a data management system (DMS) to execute a first instance of a query to obtain, from a database, first information that is responsive to the query. The DMS may identify, in response to the query being executed in an execution time that is greater than a threshold amount of time, an improved version of the query that is associated with a second execution time that is less than the threshold amount of time. The DMS may store the improved version of the query. The DMS may retrieve the improved version of the query in response to receiving a second instance of the query. The DMS may execute the improved version of the query after retrieving the improved version from storage to obtain, from the database, second information that is responsive to the query.

Abstract: A method may include: receiving an original dataset and a sensitive attribute; initializing a distilled dataset from the original dataset; initializing a classification model; sampling original dataset data and an original dataset label from the original dataset, and distilled dataset data and a distilled dataset label from the distilled dataset; providing the sampled original dataset data from the original dataset to the classification model, resulting in an original dataset prediction probability; providing the sampled distilled dataset data from the distilled dataset to the classification model, resulting in a distilled dataset prediction probability; calculating a distilled dataset cross-entropy loss for the distilled dataset prediction probability and the distilled dataset label; calculating distilled dataset gradients for the distilled dataset cross-entropy loss; calculating a distance between the gradients as a matching loss; and updating the distilled dataset with the matching loss.

Abstract: Provided are a method and system for selecting and ranking keywords, including a process through which a universe of potential keywords tied to various topics is generated and filtered. Once this is completed, search engine ranking pages (SERPs) are generated for these potential keywords. Reference text associated with topics of interest is also generated by the system of the present invention. This can be accomplished in various ways according to the teachings herein. For example, reference text can be generated using generative AI functionality. Initial reference text can be later improved upon using machine learning techniques so as to adjust reference text that is too broad or narrow in scope. Reference text and SERP results are used in connection with a model to generate semantic similarity scores which are then used for ranking and selecting keywords.

Abstract: Systems, methods, and machine-readable media to migrate data from source databases to target databases are disclosed. Data may be received, relating to the source databases and the target databases. For each source database, a migration assessment may be generated based on analyzing the data, and a migration method may be selected. A migration plan that specifies a parallel migration of a set of databases to the target databases may be created, with a first migration method to migrate a first subset of the set of databases and a second migration method to migrate a second subset of the set of databases. The parallel migration may be executed according to the migration plan may be caused so that the first subset of the set of databases is migrated with the first migration method while the second subset of the set of databases is migrated with the second migration method.

Abstract: In one embodiment, a computing device includes a memory device storing instructions, and a processing device communicatively coupled to the memory device. The processing device executes the instructions to execute a computer-implemented system configured to manage items in a self-describing data model, and generate a representation of a federated system in the self-describing data model. The representation includes logical model items having logical model item types associated with data in an external object model used by a third-party computer-implemented system. The processing device may enable communication of the items and the logical model items between a client computer-implemented system and the third-party computer-implemented system.

Abstract: Systems and methods for receiving information associated with posts to a social network are described. Posts may be associated with a location. Symbols, portions or posts, or multiple symbols may be shown on a client device in an area of a map indicating a location associated with a post. Posts may be represented by symbols, which may include shapes, and such shapes may include emojis. An amount of symbols, posts, or portions of posts displayed on a client device may be determined at least in part by an area of a map displayed on a client device.