Abstract: In accordance with various embodiments of the present disclosure, a first instance of a data intake and query system (DIQS) may receive latency data that indicates latency states of second instances of the DIQS, the latency states indicative of latencies associated with processing of event data by the plurality of second instances. The first instance may then determine overall latency state of the first instance based, at least in part, on determining number or percentage of the first instance and the second instances of the DIQS having one or more particular latency states, and determining whether the number or percentage of the first instance and the f second instances of the DIQS having the one or more particular latency states is equal to or exceeds a threshold. The first instance may then present the overall latency state of the first instance.

Abstract: Systems and methods for determining an evaluation of one or more patients is provided. User input for evaluating one or more patients is received. A commit bundle is retrieved from a commit database. An evaluation of the one or more patients is determined based on the user input using a medical ontology configured with the retrieved commit bundle. The medical ontology is separate from the commit database. Results of the evaluation of the one or more patients are output.

Abstract: Disclosed is a computer-implemented method for determining a score adjustment for a search document, comprising determining a first attractiveness model of a first document from one or more documents based on one or more user interactions associated with the first document; determining a second attractiveness model of a second document from one or more documents based on one or more user interactions associated with the second document; determining one or more pairwise comparisons of documents based on the first and second attractiveness models of the first and second documents; training an adjustment model based on the pairwise comparisons of documents; and inputting the search document into the adjustment model to determine the score adjustment.

Abstract: In an aspect a computer system is configured to: receive accelerated transfer definition data defining one or more conditions for accelerating a transfer; obtain a due date for completing the transfer; initiate the transfer in response to the earlier of: determining that at least one of the conditions for accelerating the transfer have occurred; and determining that a current date is within a defined proximity of the due date for completing the transfer.

Abstract: There is provided a system including a memory and a processor configured to stream a media content for playback to a first media device for viewing by a first user, receive, while streaming the media content, an input from the first media device indicating an insertion point in the media content selected by the first user for inserting a contextual message provided by the first user, receive the contextual message from the first media device, stream the media content for playback to a second media device for viewing by a second user, and deliver the contextual message to the second media device for viewing by the second user when streaming the media content to the second media device reaches the insertion point.

Abstract: A classification device includes processing circuitry configured to obtain operation logs describing operation content for a window on a terminal screen, classify the operation logs into a plurality of groups, using a document classification method, based on the operation content of the operation logs, and assign words characteristic of respective groups as labels to these groups, and cause an output device to output the operation logs assigned the labels.

Abstract: File system performance enhancement is provided. Information related to a container of the computer accessing a file in a layer of a file system of an image corresponding to the container is recorded to form recorded file system layer access information. The recorded file system layer access information is shared with another file system of a container image corresponding to a different container on the computer. The container image is a same image as the image corresponding to the container that accessed the file to perform an operation associated with a cloud application.

Abstract: Search integration is described. The actions include receiving, by one or more processors, a query. The actions include identifying search results that are responsive to the query. The actions include identifying, based on the query and the search results, structured data to supplement the search results, wherein the structured data is generated from binary table data that is received and deserialized by one or more processing modules. The actions include processing the structured data and the search results. The actions include providing, for output, the processed search results and the processed structured data results.

Abstract: Recommending database access patterns for transactions in microservices is provided. A recommendation of a particular database access pattern to improve access by transactions to data in fields of tables in a database corresponding to a microservice is generated based on analysis of field access graphs for the tables accessed by the transactions. The recommendation of the particular database access pattern is output. The particular database access pattern is implemented to improve access by the transactions to the data in the fields of the tables in the database corresponding to the microservice to improve performance of the microservice based on user input and read view implementation guidance.

Abstract: Aspects of distributed ledger technology are leveraged to verify subrogation settlements. In particular, two parties to a subrogation claim provide cryptographic hashes to a subrogation demand smart contract stored at an address on a blockchain. The subrogation demand smart contract determines that the parties have reached an agreement by determining that the cryptographic hashes match. A settlement amount from the subrogation claim may be appended to a set of settlement amounts to determine a net settlement amount to facilitate a single payment between the parties on a periodic basis, such as daily, to alleviate the need for the parties to send or receive a payment for each individual settlement amount.

Abstract: Described herein are mechanisms to allow users to access functionality of applications in a suite of applications. In a first aspect, when a query relating to functionality of an application is received from a user, an index containing both top-level and sub-level functionality is searched. Results are ranked using a trained machine learning model using both context describing user interactions and the search results. A subset of the ranked results are presented to the user as options. In a second aspect the index can comprise entries describing functionality from other applications so that results presented to the user can include cross-application functionality. In a third aspect, the index can be searched using the context prior to receiving a query and adjusting the user interface based on the results. In a fourth aspect, the system can recommend other applications and/or devices that are better suited to a user's intent.

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: A system and method is described for labelling data for trigger identification. The system and method comprising receiving data, transforming the data, extracting content from the data, processing data content through a classification machine learning model to receive a label, and trigger a secondary system based on the label. The system and method may further include maintaining a database of labeled data.

Abstract: Systems and methods for generating a machine-learning (ML) model for extracting information from one or more electronic documents, where the ML model can be used as a data object, which can be part of a database command or as part of a document information extraction process that is continuously running (e.g., document information extraction pipeline).

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: 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: 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: 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: 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: 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.