Abstract: An apparatus for optimal zone strategy selection, wherein the apparatus comprises a processor and a memory configuring the processor to receive user data; classify the user data to a plurality of target classes; generate a user goal as a function of the plurality of target classes; generate a plurality of zone strategies based on the user goal as a function of identifying a zone strategy score for each of the plurality of zone strategies; determine follow-through data as a function of ranking the plurality of zone strategy scores and the zone strategies; populate a user interface data structure comprising a visual representation of the zone strategies and the follow-through data; and transmit the user interface data structure to a display device communicatively connected to the at least a processor to display the visual representation of the zone strategies and the follow-through data using a graphical user interface (GUI).

Abstract: In some examples, a data management system processes snapshots of a distributed file system, the distributed file system having files, each file comprising multiple data chunks. The data management system performs operations including storing file-to-chunk mapping in file system metadata; creating, for each chunk, a chunk generation ID by associating each chunk with a file system generation ID; in a next-generation snapshot of the distributed file system, incrementing, for all chunks in the next-generation snapshot, the respective chunk generation IDs; and taking a snapshot of the file system metadata and storing an updated file-to-chunk mapping associated with the next-generation snapshot.

Abstract: A system and method for creating a remediation plan with in-context learning (ICL) to a large language model (LLM) involves accessing pieces of content from a corpora and calculating similarity scores between selected content and the corpora. If the similarity score exceeds a set threshold, static metadata—such as authorship, file name, file size, last updated date, or source location—is retrieved. Dynamic metadata, including word count, sentence count, grammar correctness, number of citations, or layout classification, is also generated. Based on static and dynamic metadata, a remediation action is determined, which may involve merging content, prioritizing one piece over another, or ignoring certain content. A remediation prompt is then created and sent to the LLM to generate a preferred output. The process continues by accessing additional unprocessed content and repeating until a time limit expires, computational resources are consumed, or all content has been processed.

Abstract: A recommendation system includes a content similarity analyzer configured to determine a first set of content item identifiers similar to a set of viewed content items based on respective similarity scores and add them to a first list. A similar user content extraction module identifies a set of similar user identifiers from a user similarity database; obtains, based on respective viewing histories of the set, a second set of content item identifiers; and adds them to the first list. The recommendation system includes a content filter configured to select a subset of content item identifiers from the first list based on the corresponding similarity scores between content item identifiers of the first list and a viewing history. The content filter is configured to transmit the subset of content item identifiers for display of the corresponding content items via a web portal on a user interface of a first user device.

Abstract: Certain aspects of the disclosure provide techniques for categorization by a device. An example method includes receiving input information regarding a plurality of classification targets and a plurality of categories for classification of the plurality of classification targets; generating a plurality of embeddings for the input information using a first model, the plurality of embeddings including: a set of first embeddings associated with the plurality of classification targets, and a set of second embeddings associated with the plurality of categories; determining that a similarity score for the set of first embeddings and the set of second embeddings fails to satisfy a threshold; generating, based on the similarity score failing to satisfy the threshold and using a graph neural network (GNN), a classification of the plurality of classification targets in accordance with the plurality of categories; and outputting information regarding the classification.

Abstract: A device for using message identifiers for Publish/subscribe messaging deduplication is described. The system may fetch one or more sets of data records from a data source, and each data record is associated with a message identifier. The system may store the one or more sets of data records in a data file, which is associated with a metadata comprising the message identifier, a file path and a row number for each data record. The system may determine whether one or more of the data records are duplicated based on the associated message identifiers. In response to determining that the one or more data records are duplicated, the system may generate a second metadata comprising the file paths and row numbers associated with the duplicated data records.

Abstract: A processor-implemented method is disclosed.

Abstract: Embodiments of the present disclosure are directed to monitoring and responding to social media content according to one embodiment of the present disclosure. Monitoring and responding to social media content can comprise reading content of a social media source and identifying a sub-set of content from the content of the social media source for response based on a model defining content for which a response is to be prepared. One or more natural language responses to the identified sub-set of content can be generated based on a model defining responses and a knowledge base of information. Each natural language response can comprise factual information from the knowledge base of information. The generated one or more natural language responses can be submitted to the social media source in response to the identified sub-set of content.

Abstract: Disclosed herein are systems and method for data chunking. In one aspect, a method includes consecutively scanning each respective byte in a byte stream of data. The method includes in response to detecting a first amount of adjacent bytes with values arranged in a decreasing order, marking a cut-off point of a data chunk comprising at least the adjacent bytes. The method includes in response to detecting a second amount of bytes with values arranged in an increasing order, executing a jump mechanism that skips scanning of a fixed amount of bytes after the bytes with values arranged in the increasing order. The method includes subsequent to scanning the byte stream in entirety, outputting a plurality of cut-off points of identified data chunks.

Abstract: A KID's computer system is configured by PARENT-controlled software, giving each PARENT the power and responsibility to control the social media content being presented to their KID. The PARENT prescribes the criteria for action to be taken; and the PARENT prescribes the action to be taken by the KID's computer system. The PARENT-prescribed criteria comprises a list of BAAE-type states, e.g., emotional state. If one of these states is induced in the KID when they accessed the content from a Social Media Platform, then it triggers a PARENT-prescribed action. The list of possible PARENT-prescribed actions comprises at least the following: blocking the content, informing the KID, the PARENT, the Social Media Platform, School Authorities, Law Enforcement, Health Authorities of the KID's state, and archiving the event-data. The archived event-data is analyzed to discover harmful behavior patterns, e.g., lack of self-control, exhibited by the KID vis-à-vis social media content.

Abstract: System and method for generating and displaying data pipelines according to certain embodiments. For example, a method includes: receiving a natural language (NL) query; receiving a model result generated based on the NL query, the model result including a query in a standard query language, the model result being generated using one or more computing models; and generating the data pipeline based at least in part on the query in the standard query language, the data pipeline comprising one or more data pipeline elements, at least one data pipeline element of the one or more pipeline elements being corresponding to a query component of the query in the standard query language.

Abstract: Methods, systems, and non-transitory computer readable media are configured to perform operations comprising receiving metadata associated with a snapshot of data; extracting one or more textual features from the metadata; and determining a classification of the snapshot based on the one or more textual features.

Abstract: Disclosed implementations for providing a description in a search result for a resource providing video content. A resource providing video content is received. A query having the resource as a relevant result is generated. A description of the resource is generated by processing a prompt through a generative model. The prompt includes the query and descriptive content related to the video content. The query and the description are stored based on a groundedness score meeting a groundedness threshold. The groundedness score indicates an alignment between the description and the prompt. The description is provided in a search result that includes the resource.

Abstract: One implementation of the disclosure is directed to an Information Technology Service Intelligence (ITSI) that provides methods having operations of obtaining historical data for a metric including a plurality of time-series data sets spanning a common time period and each associated with a distinct entity, generating an aggregated time-series data set by applying an aggregation function to corresponding data points in each of the plurality of time-series data sets, selecting a seasonality pattern for the aggregated time-series data set from a plurality of candidate seasonality patterns by computing a silhouette score for each of the plurality of candidate seasonality patterns in view of the time-series data set, wherein a selected seasonality pattern has a highest silhouette score, and partitioning the aggregated time-series data set into subsequences according to the selected seasonality pattern, and generating a plurality of severity level thresholds for each subsequence.

Abstract: Disclosed are a method and apparatus for determining a given template of a form used by a filled in instance of that type of form from amongst a great number of form templates (a hundred or more). The given instance is evaluated by a neural network that has been trained by a single example of each template in order to reduce the total number of templates down to a manageable amount. Given a list of closest matching templates, the instance is aligned to each of the closest matching templates. The comparison generates a match score. The form template having the greatest match score is the correct form template. Filtering the instance through a one-shot learning neural network before performing a precise comparison enables the process to scale to any number of template forms.

Abstract: Updating of object model data of interface elements based on emission scores includes receiving first interaction data associated with an interaction session between a specific user and one or more interface elements of an operation of an application. A user emission score associated with the interaction session is generated based on the interaction data. A first cluster from a plurality of clusters is identified for the specific user based on the user emission score and cluster data. A cluster emission score associated with the first cluster is generated based on the user emission score and the cluster data associated with the first cluster. Further, object model data associated with each interface element of the one or more interface elements is received. The object model data associated with at least one interface element is updated. The updated object model data is output.

Abstract: A data store comprises a commit management map including an identifier of a distributed transaction. A control method executed by an adapter coupled to the data store includes: alternate processing of, temporarily storing the reception query, and causing a transaction on the data store side to execute the reception query; perpetuation processing of determining whether or not commit is possible using lock information and perpetuating the GXID to be committed and the temporarily stored reception query in a case where commit is possible; settlement processing of causing the transaction on the data store side to execute a GXID addition query that is a query that adds the GXID to be committed to the commit management map and committing the transaction on the data store side; and store restart processing of the adapter starting a new transaction at the data store for a distributed transaction in an in-doubt state.

Abstract: Aspects of the subject technology relate to systems, methods, and computer-readable media for dynamically filtering time series data using multiple conditions in a structured query environment. An example method can include receiving, in a structured query environment, a data request, which includes a plurality of conditions associated with a time period. The example method further includes accessing a database, which is configured to store time-series data corresponding to the time period and mapping a set of dates based on the plurality of conditions associated with the time period. The example method also includes applying a sequence of filters corresponding to the plurality of conditions, onto the set of dates, within a single query to the database and obtaining, from the database, data corresponding to filtered dates.

Abstract: In various embodiments described herein, a visualization system receives message requests from client devices, wherein the message requests comprise at least location data that identifies a location of a client device, and media content, wherein the media content includes at least one of image data, audio data, and video data. In response to receiving the message requests that comprise the media content, the visualization system analyzes and parses the media content to detect one or more tags embedded within the media content. In response to detecting the tag, the visualization system identifies a campaign or account referenced by or associated with the tag. Based on the identification of the campaign based on the tag within the media content, the visualization system determines a distribution of the campaign based on the location data from the message request.

Abstract: Techniques for generating and leveraging a multi-snapshot HNSW index are provided. In one technique, multiple snapshots of an HNSW index that was generated based on a vector table comprising an initial set of vectors are stored. Each of snapshots has a different build time and is associated with a shared journal that stores a plurality of changes to a plurality of vectors in the vector table. A latest snapshot of the plurality of snapshots is identified. The shared journal is identified. It is determined, based on one or more criteria, whether to generate a new snapshot based on the latest snapshot and the shared journal. In another technique, in response to receiving a vector query that is associated with a timestamp, a particular snapshot is selected from the snapshots based on the timestamp. The vector query is executed against the particular snapshot and the shared journal.