Abstract: A system and method for generating synthetic datasets includes receiving, via an application programming interface (API) of a remote generative database service, a generative database query for obtaining synthetic data samples statistically representative of a sensitive dataset, searching a generative model data structure comprising a plurality of generative model nexuses based on a generative model election request derived from the generative database query, wherein the searching returns a generative model for fulfilling the generative database query, generating a synthetic dataset using the generative model returned from the searching based on a plurality of generative query parameters extracted from the generative database query, and returning the synthetic dataset as a result to the generative database query.

Abstract: Embodiments of the present disclosure provide a method and apparatus for reset command configuration, a device, and a storage medium, the method, applied to an editor of target software, includes: starting a command group storage unit and starting a snapshot session through the inputted startGroup command; directly performing the reset command configuration on the target software in an command-type manner through the inputted operation execution command; converting change information of an object in the snapshot-type session into a command pair through the snapshot capture command, pressing the command pair into the command group storage unit, and using all command groups of the command pair as a reset command to realize performing the reset command configuration on the target software in the snapshot-type manner, thereby achieving that the target software supports both the command-type reset command configuration and the snapshot-type reset command configuration.

Abstract: A disclosed database system and enhanced methods implement enhanced mini-plans and dynamically changing a query mini-plan with trustworthy Artificial Intelligence (AI) to improve query execution performance in a database system. An AI cost model evaluates candidate mini-plans for executing a query. AI truth monitors evaluate the execution of the mini-plans, such as predicted input factors and adjusted mini-plans of one or more AI running data models. The AI truth monitors provide feedback to adjust the AI cost model based on evaluating the execution of the mini-plans. The AI truth monitors validate adjusted mini-plans, provide feedback to the AI cost model with improved overall prediction accuracy, and enhanced mini-plans to gain query performance.

Abstract: Embodiments of the disclosed technologies provide solutions for automatically reading digital electronic documents that contain tables and correctly extracting table data, rows and columns from the documents with high accuracy and high throughput. Embodiments are capable of converting a table portion of a read-only document to a searchable, editable data record using text rectangle (TR)-level numerical data that indicates probabilities of TRs belonging to canonicals and at least one convolutional neural network (CNN) that processes the TR-level numerical data to produce table-level numerical data.

Abstract: Software architectures relating to machine learning (e.g., relating to classifying sequential text data. Unlabeled sequential text data may be produced by a variety of sources such as text messages, email messages, message chats, social media applications, and web pages. Classifying such data may be difficult due to the freeform and unlabeled nature of text data from these sources. Thus, techniques for training a machine learning algorithm to classify unlabeled text data in freeform format. Training is based on generation of labelling functions from lexical databases, applying the labelling functions to unlabeled text data in an unsupervised manner, and generating trained classifiers that accurately classify the unlabeled text data. The trained classifiers may then be implemented classify text data accessed from the variety of sources. The present techniques provide high-quality and efficient labeling of unlabeled text data in freeform formats.

Abstract: Apparatus and associated methods relate to mitigating data-stream dropout in a serial data-stream. A time-sequence of messages of the serial data-stream is received, each containing a data packet communicating an action. Validity of each of the time-sequence of messages received is determined. After receiving each valid message, a plurality of future actions is created based at least in part on the valid message received. The plurality of future actions corresponds to a plurality of future data packets of the time-sequence of messages. After receiving each valid message, the action communicated in the valid message received is performed. After receiving each invalid messages, a next one of the set of sequential future actions created is instead used in place of any action communicated in the data packet of the invalid message received.

Abstract: Software feature metadata objects and software artifact search, identification, and tracking is provided herein. A software artifact can have an associated software feature metadata object. A software feature metadata object can include metadata describing or defining at least in part the software artifact. The software feature metadata object can include one or more defined queries for identifying the software artifact in applications or programming code. The software feature metadata object can include one or more identifiers for composite software artifacts which integrate the software artifact corresponding to the software feature metadata object. The software feature metadata object can be accessed to obtain metadata about the corresponding software artifact for tracking usage, integration, or other activities, which can be provided for reporting or analysis.

Abstract: Methods, systems, and media for searching for video content are provided. In some embodiments, the method comprises: receiving one or more characters entered into a first query field by a user; determining a predicted search query based on the one or more received characters; determining a plurality of suggested search queries based on the one or more received characters; causing the predicted search query to be presented in the first query field and at least a portion of the plurality of suggested search query to be presented in a second query field, wherein the predicted search query is combined with the one or more received characters in the first query field; searching a database of videos based on the predicted search query; causing a plurality of video content items from the database of videos responsive to the predicted search query to be presented; and causing, without user interaction, a first video content item from the plurality of video content items to be played back.

Abstract: A plurality of images are received from one or more social media platforms associated with a user. For a selected image of the plurality of images, a plurality of text descriptions are generated. The plurality of text descriptions are computer-generated captions that describe features of the selected image of the plurality of images. The plurality of text descriptions are processed through a natural language processing model. Based on processing, a plurality of interest contexts are derived from the plurality of text descriptions. A mapping of each of the plurality of interest contexts to one or more predefined categories associated with an online marketplace is generated. Based the mapping of each of the plurality of interest contexts to the one or more predefined categories, a user device associated with the user is caused to display an app page or web page associated with the one or more predefined categories.

Abstract: Data storage operations, including content-indexing, containerized deduplication, and policy-driven storage, are performed within a cloud environment. The systems support a variety of clients and cloud storage sites that may connect to the system in a cloud environment that requires data transfer over wide area networks, such as the Internet, which may have appreciable latency and/or packet loss, using various network protocols, including HTTP and FTP. Methods are disclosed for content indexing data stored within a cloud environment to facilitate later searching, including collaborative searching. Methods are also disclosed for performing containerized deduplication to reduce the strain on a system namespace, effectuate cost savings, etc. Methods are disclosed for identifying suitable storage locations, including suitable cloud storage sites, for data files subject to a storage policy.

Abstract: In an approach for detecting non-obvious relationships between entities from visual data sources, a processor calculates a co-occurrence frequency score for an entity pair from visual data. A processor calculates a distance proximity score for the entity pair from the visual data. A processor determines an event type in the visual data. A processor determines a timeline relationship in the visual data. A processor calculates a relationship score based on the co-occurrence frequency score, the distance proximity score, the event type, and the timeline relationship. A processor detects a relationship between the entity pair based on the relationship score.

Abstract: A method for processing information includes receiving a feature set for an application in a medical system, determining a disconnection between the application and a monitoring station, and determining a type of the disconnection based on information in the received feature set. The type of disconnection may be determined by inputting the feature set into a classifier trained to automatically determine the type of disconnection based on the information in the feature set. Information indicative of the type of disconnection may then be input into a rules-based engine, which generates a recommendation for remediating or otherwise managing the classified disconnection.

Abstract: An apparatus for expanding contacts for a social networking platform includes at least a processor communicatively connected to a user device and a memory communicatively connected to the processor. The memory contains instructions configuring the at least a processor to determine potential contacts for a user with an automated process including identifying a user identification on an immutable sequential listing, retrieving activity data linked to the user identification, retrieving a body of sets of user activity data as a function of the activity data, and identifying potential contacts by generating a match function between the user and each set of the sets of the user activity data. Processor further receives a selection input from the user device selecting a contact of the potential contacts, delivers an information request about the user to a selected contact device, and receives an information response from the selected contact device.

Abstract: Disclosed herein is an apparatus for analyzing a video shot. The apparatus includes at least one program, memory in which the program is recorded, and a processor for executing the program. The program may include a frame extraction unit for extracting at least one frame from a video shot, a shot composition and camera position recognition unit for predicting shot composition and a camera position for the extracted at least one frame based on a previously trained shot composition recognition model, a place and time information extraction unit for predicting a shot location and a shot time for the extracted at least one frame based on previously trained shot location recognition model and shot time recognition model, and an information combination unit for combining pieces of information, respectively predicted for the at least one frame, for each video shot and tagging the video shot with the combined pieces of information.

Abstract: According to certain aspects of the disclosure, a computer-implemented method may be used for analytics integration into electronic mediums. The method may include determining at least one insight discovery function from a plurality of insight discovery functions on a user device and enabling a software module based on the selection of the at least one insight discovery functions. Additionally, the method may include determining at least one key term based on the enabled software module, and determining at least one electronic data card associated with the at least one key term. Additionally, the method may include presenting the at least one data card to the user device based on a user interaction with the at least one insight discovery function on the user device.

Abstract: A virtual assistant server receives a user input from a virtual assistant interface available on a client system associated with a user identified by a user identifier. Upon receiving the user input, the virtual assistant server creates a search network of repositories not associated with the user identifier by determining, for the received user input, a priority score of each repository not associated with the user identifier based on interactions of the user identifier through the virtual assistant interface. Further, the virtual assistant server searches, for the received user input, in a repository associated with the user identifier and in the repositories in the search network. Based on the searching, a group of one or more results corresponding to the received user input are identified and returned to the client system associated with the user identifier.

Abstract: A data processing system implements obtaining query parameters for a query for content items in a datastore, the query parameters including attributes of content items for which a search is to be conducted; obtaining a first set of content items from a content datastore based on the query parameters; analyzing the first set of content items using a first machine learning model trained to generate relevant content information that identifies a plurality of relevant content items included in the first set of content items; and analyzing the plurality of relevant content items using a second machine learning model configured to output novel content information, the novel content information including a plurality of content items predicted to be relevant and novel, the novel content information ranking the plurality of content items predicted to be relevant and novel based on a novelty score associated with each respective content item.

Abstract: A method comprising receiving, from a first enterprise system, a series of first language commands written in a first language to control a first data flow of first data, the first data being from a first and a second data source, the first series of first language commands indicating first functions to be performed including collection of first data, storage of the first data into a first data warehouse, and application of one or more first applications on the stored first data, the first and second data sources being unrelated to each other and being remote from the first enterprise system and the data warehouse, translating the series of first language commands into first translated commands that may be provided to the first and second data sources as well as the first data warehouse to control the first data flow.

Abstract: A method is provided. The method includes one or more of obtaining client device data including a plurality of facts from a client device, limiting the client device data according to selection criteria, comparing, using a neural network, the limited client device data to categorized historical data, determining, using the neural network, one or more closest matches between the limited client device data and the categorized historical data, and selecting, on the client device, content of interest from the one or more closest matches. Each fact includes an entity, an observation, and an object. Limiting the client device data includes reviewing the entity, observation, and object for each fact and one or more of eliminating facts having an entity, observation, or object that does not meet the selection criteria and removing data from entities, observations, or objects that uniquely identifies a user associated with the client device.

Abstract: A system includes computer-readable media having memory, one or more processors, and instructions in the memory that, when executed by the one or more processors, cause the processor(s) to: generate an archive container, a cooked container, an ingest container, and an index container; receive, in the ingest container, a plurality of time series data elements; identify a data format for each of the time series data elements; divide the plurality of time series data elements into a plurality of data sub-elements based on a corresponding append binary large objects (blobs) contained in the cooked container; generate, statistical data for the plurality of time series data elements for each of one or more index blobs contained in the index container; and output: the statistical data to the index container; the plurality of data sub-elements to the cooked container, and the plurality of time series data elements to the archive container.