Abstract: A computer system processes dining context data across multiple time scales to generate personalized dining recommendations. The system includes a temporal processing engine that simultaneously analyzes both immediate and historical dining data using multiple time-scale processors while maintaining temporal coherence. A dining context integration engine extracts and organizes features related to individual preferences and group dining dynamics, ensuring state continuity. A fusion engine combines outputs from the temporal processors with contextual representations to generate informed dining recommendations. These components work cooperatively to integrate real-time and historical dining patterns, enhancing dining experiences through adaptive and context-aware recommendations.

Abstract: Techniques for use in identifying one or more concepts in a knowledge representation (KR). The techniques include obtaining user context information associated with a user, wherein the user context information comprises a plurality of words. Also included are semantic disambiguation techniques comprising obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and disambiguating between a first and second concept in a knowledge representation (KR) associated with a first meaning of the first portion. Semantic disambiguation techniques further include obtaining user context information associated with a user, wherein the user context information comprises a first portion and a second portion different from the first portion; and disambiguating between a first concept and second concept in a knowledge representation (KR) using a measures of dominance and semantic coherence.

Abstract: A memory device may include logical units configured to store data, wherein the logical units are identified by corresponding logical unit numbers (LUNs) and are associated with corresponding LUN queue groups. Each LUN queue group may include LUN queues that are each associated with a respective intra-LUN priority level that indicates a priority of a LUN queue within a LUN queue group. The LUN queues are each associated with a respective execution priority level that indicates a priority for execution of commands in a LUN queue across LUN queue groups. A quantity of intra-LUN priority levels may be greater than a quantity of execution priority levels. A LUN scheduler may be configured to select and transfer commands from LUN queue groups to the execution queue group based on intra-LUN priority levels. A command executor may be configured to execute commands from the execution queue group based on execution priority levels.

Abstract: A vector friendly instruction format and execution thereof. According to one embodiment of the invention, a processor is configured to execute an instruction set. The instruction set includes a vector friendly instruction format. The vector friendly instruction format has a plurality of fields including a base operation field, a modifier field, an augmentation operation field, and a data element width field, wherein the first instruction format supports different versions of base operations and different augmentation operations through placement of different values in the base operation field, the modifier field, the alpha field, the beta field, and the data element width field, and wherein only one of the different values may be placed in each of the base operation field, the modifier field, the alpha field, the beta field, and the data element width field on each occurrence of an instruction in the first instruction format in instruction streams.

Abstract: The provides solutions for determining an elected search head captain is unqualified for the position, identifying a more qualified search head, and transferring the captain position to the more qualified search head. A method is provided that includes referencing qualification parameters in an elected search head captain, determining whether the newly elected search head captain is qualified for the position based on the parameters, identifying a more qualified search head to be the search head captain if the newly elected search head captain is determined to be unqualified for the position, and transferring the position of captain to the more qualified search head. The qualification parameters may include, for example, a pre-determined static flag set by an administrator of the search environment, and configuration replication status that corresponds to the most recent configuration state of the search head as recorded by the previous search head captain.

Abstract: A computer-implemented method includes receiving data records from a plurality of different data sources, in which the data records include information regarding elements or components in one or more systems; consolidating the data records; extracting information from the consolidated data records to identify a plurality of nodes and connections between the plurality of nodes in the one or more systems; storing information identifying the plurality of nodes and the connections; and visually presenting the plurality of nodes and the connections in a user interface.

Abstract: A system for processing and integrating contextual information across multiple time scales simultaneously analyzes immediate and historical data. The system comprises three main components working together to maintain temporal coherence. A temporal processing engine processes input data at different time scales using multiple processors, each dedicated to a specific time horizon. A context integration engine extracts and organizes contextual features from the input data, generating representations for different types of context while maintaining state information across these context types. A fusion engine combines the outputs from the temporal processors and integrates them with the context representations to generate coherent, unified outputs. The three engines operate cooperatively to ensure temporal consistency while processing context across multiple time scales.

Abstract: Arrangements for intelligent regression detection are provided. Initial parameters including a first commit and a second commit may be received and a midpoint may be identified. A test may be executed at the midpoint. A regression detection algorithm may be used to determine whether a regression is present at the midpoint. The regression detection algorithm may automatically identify patterns from test results indicative of regressions and detect regressions based on the identified patterns. The midpoint may be set as the first commit or the second commit based on whether the regression is present at the midpoint. A new midpoint may be identified between the updated initial parameters. A test may be executed to determine whether the regression is present at the new midpoint. A search space of commit points may be automatically iteratively refined using the new midpoint at each iteration until a single commit causing the regression is identified.

Abstract: A method, system and computer program product of processing a document from an electronic_historical digital archive and enabling electronic semantic searching, may include: electronic_pre-processing the electronic_document; electronically enriching, and enabling electronically_semantic searching of the electronic document, which may digitize and make machine readable. Electronic pre-processing is a quality check of the process and not of the results. Electronic pre-processing means the translation/transformation quality of the document may or may not require alterations after translation/transformation. Electronic p re-processing embodiments may make searchable by LLMs, electronic score quality of electronically searchable document, electronically update the electronically searchable document to create a better score quality, and may include retrieval-augmented generation (RAG)-encoding, embedding LLM scoring vector and object semantics; and/or store in, an electronic database such as, e.g.

Abstract: A computer-implemented method is provided for an automated extract, transform, and load process for a target database comprising linked data. During the data transformation phase linked data elements are added as data to a data set.

Abstract: A batch process operates on structured data in multiple tables, including a first and a second source table, and a first and a second processing table. An additional key is added within each natural key to at least the second source and processing table for identifying a sequence of rows for updating.

Abstract: A data recording and annotation system includes data recording device for generating a data record. After the data recording device receives a request to review the one or more data records, the data recorder provides the one or more data records to the requester. After the data recorder receives an approval or annotation made about the data record, the data recorder generates a revised data record including information from the data record and from the approval or annotation. Then the revised data record is stored on the data recording device. The data records may be accessed at either the data generating device itself, or through a remote connection.

Abstract: A computer-implemented method for regulating delivery frequency of outbound communications. The method includes receiving message context data comprising one or more of a user identifier, a client identifier, a campaign identifier, a channel identifier, a label identifier, and a trigger identifier. A counter-field identifier is determined that encodes the channel identifier, label identifier, trigger identifier, campaign identifier, and a temporal-interval indicator. A counter field identified by the counter-field identifier is created. A value stored in the counter field is incremented through an atomic operation. The value is compared with a limit stored in a rule set. An allow signal is output when the value does not exceed the limit and a suppress signal is output when the value exceeds the limit. An engagement-counter record is updated to the in-memory database.

Abstract: Provided are systems and methods that rely on machine learning to recommend employment opportunities. In one example, a method may include identifying, via execution of a first machine learning model, income data and spending data of a user, identifying, via execution of a second machine learning model, skill attributes of the user, determining, via execution of a third machine learning model, a recommended job for the user, where the determining comprises inputting the outputs from the first and second machine learning models into the third machine learning model, and displaying, via a user interface, a description of the recommended job.

Abstract: A computer-implemented method including receiving a query from a user related to legal information. The method also can include performing an initial retrieval of document chunks from a corpus of legal documents. The method additionally can include applying a cross-encoder model to generate relevance scores for the document chunks. The method further can include filtering the document chunks based on a quality threshold. The method additionally can include calculating a combined score for each remaining document chunk of the document chunks based on a respective relevance score of the relevance scores, temporal relevance score, and a document type importance score. The method also can include selecting a subset of top-scoring document chunks based on the combined score. The method additionally can include generating a response to the query based on the subset of the top-scoring document chunks.

Abstract: A system and method include receiving a plurality of elements in a data array to be sorted, assigning the elements a sequential index value, computing an amount of additional memory needed to sort the elements, creating a Linked-Array Tournament Tree (LATT), storing the LATT in the allocated amount of additional memory, initializing the LATT, initializing a number of iterations, initializing a next sorted index position in the data array, determining from the LATT, the index value of a champion element from all the winners of the pairwise comparisons, swapping the champion element with an element at the next sorted index position in the data array, updating the LATT responsive to the swapping, updating the next sorted index position, repeating a plurality of times, and outputting the data array having the elements in a sorted order.

Abstract: Monitoring devices, such as air particle counters, having mesh network capabilities are described for implementation in environmental monitoring within a facility. The air particle counters run samples at various facility locations based on a standard operating procedure (SOP). Each air particle counter can opportunistically connect with one or more other air particle counters using mesh networking. Data from samples run by and any new or updated SOP received at the air particle counters can be distributed via database replication across the other air particle counters using the mesh networking such that each air particle counter has a copy of the sample data and a current SOP within its database. A dashboard user interface displaying a hierarchical representation of the SOP and an associated compliance status with the SOP can be generated and updated based on data received from the air particle counters to facilitate SOP management.

Abstract: A data processing service receives a request from a user. The request specifies a task for generating embedding vectors to represent a target dataset using a target embedding model. The service applies an automatic pipeline to the target dataset, which pre-processes the target dataset to generate batches of the target dataset. Each batch includes a plurality of data chunks in the target dataset. The automatic pipeline assigns computing resources to each batch of the target dataset; and applies, by the assigned computing resources, the target embedding model to each batch to generate the embedding vectors. Each embedding vector represents a data chunk of the target dataset in a latent space and is incrementally updated based on an update to a corresponding data chunk represented by the embedding vector. The configuration stores the generated one or more embedding vectors in a vector database.

Abstract: An apparatus includes at least one processing device configured to monitor input-output operations for a storage system, the storage system including a memory maintaining a log structured merge tree cache for a log structured merge tree and one or more bloom filters, each of the one or more bloom filters being associated with one or more segments of the log structured merge tree. The at least one processing device is also configured to determine, based at least in part on the monitored input-output operations, whether one or more bloom filter size adaptation trigger conditions have been met. The at least one processing device is further configured, responsive to determining that at least one of the one or more bloom filter size adaptation trigger conditions has been met, to adjust one or more parameters controlling a size of at least one of the one or more bloom filters.

Abstract: Revising data management indices by defining a plurality of data entity buckets, assigning bucket hash values to each data record according to the plurality of data entity buckets, generating a record index including data record bucket membership data, determining a combined record score for each data record according to the bucket membership data, revising data record relationship indices of a data management system according to the combined record score of a data record, and responding to a user query according to the record index including the revised record relationships.