Abstract: A computer-implemented method uses a context node to identify sister nodes. The method includes receiving, by a processor, input data. The input data includes a plurality of messages, each message containing a set of message data. The method further includes, generating, by a pattern detector, and based on the input data, a network graph, where the network graph includes a plurality of nodes. The method also includes selecting a first context node. The method includes determining a first pattern for the first context node. The method further includes identifying, based on the first pattern, a first sister node. The method also includes outputting, by a network interface, the first sister node and the network graph.

Abstract: A computer-implemented method to automatically identify hotspots in a network graph. The method includes receiving, by a processor, input data, wherein the input data includes a plurality of messages, each message containing a set of message data. The method further includes generating, by a pattern detector, and based on the input data, a network graph, wherein the network graph includes a plurality of nodes. The method also includes determining a first risk indicator for each of the plurality of nodes. The method includes assigning a first weight to the first risk indicator for each of the plurality of nodes. The method further includes identifying a first hotspot in the plurality of nodes, wherein the first hotspot is based on the first weight of the first risk indicator of a first node. The method also includes outputting, by a network interface, the first hotspot and the network graph.

Abstract: Approaches presented herein enable identification of routine communication content. More specifically, a communication between one or more users is received. Words or phrases in the communication that are contained in a database of words or phrases related to misconduct are identified. The identified words or phrases are removed from the communication to create a set of remaining words. The set of remaining words are analyzed to predict the likelihood of the removed words or phrases appearing in the communication, such that a confidence level of the prediction is determined. In response to the determined confidence level being high, the identified words or phrases in the communication are classified as routine.

Abstract: A computer-implemented system, method and computer program product for preparing alert reports that includes: receiving an override request to override an insight used to prepare the alert reports; determining, determining one or more execution pipelines used to prepare the alert reports that used the insight that is the subject of the override request; determining one or more impacted pipeline runs that were executed to prepare the alert reports that used the insight that is the subject of the override request; updating the one or more execution pipelines used to prepare the alert reports; and generating new alert reports, wherein generating the new alert reports comprises re-running the one or more impacted pipeline runs using the one or more updated execution pipelines wherein the insight that is the subject of the override request is overridden.

Abstract: A computer-implemented system, platform, computer program product, tool, and/or method for re-running alert reports that includes: identifying an alert report to be rerun; collecting information on the alert report; gathering information on the configuration of a data analytics pipeline that generated the alert report; gathering data used to generate the alert report; recreating a regenerated data analytics pipeline based upon the information gathered on the configuration of the data analytics pipeline that generated the alert report; running the regenerated data analytics pipeline using the gathered data to create a rerun alert report; and optionally comparing the rerun to the original run including optionally generating a visual display of the results including in an aspect creating a side-by-side comparison of the tasks.

Abstract: A method for detecting and affirming intent to consume a supplement includes: at a wearable device worn on a hand of a user, broadcasting a wireless interrogation signal; and receiving an inbound wireless identifier responsive to the wireless interrogation signal. The method also includes, in response to the inbound wireless identifier matching a tag identifier linked to a supplement in a user profile associated with the user: detecting proximity of the supplement to the user; predicting intent of the user to consume a dose of the supplement; retrieving a consumption window for the supplement from a supplement regimen in the user account; and. in response to the current time falling outside of the consumption window, vibrating the wearable device according to a second vibration pattern during a haptic consumption avoidance cycle to prompt the user to delay consumption of the supplement.

Abstract: A computer-implemented system, platform, computer program product, tool, and/or method for capturing data and metadata for providing traceability of data analytic pipeline runs that includes: triggering a first pipeline run; obtaining a pipeline configuration for the first pipeline run, including one or more tasks; capturing and storing the pipeline configuration and starting inputs for the first pipeline run; executing the first pipeline run; capturing, before each task in the first pipeline run is executed, input data and input metadata for each task; capturing, after each task in the first pipeline run is executed, output data and output metadata for each task; and capturing the alerts for the first pipeline run.

Abstract: In an approach to facilitate contactless remote shopping assistance, a computer-implemented method includes one or more processors configured for receiving first order data from a user device corresponding to an order of items to be retrieved from a parking lot of a retail entity proximate to a retail entity location, transmitting the first order data to the retail entity, and assigning the order to a mobility device stationed at the retail entity. The method further includes transmitting order retrieval instructions to the mobility device causing the mobility device to navigate the retail to secure the items, receiving an indication that the mobility device secured the items, and transmitting order delivery instructions to the mobility device. The method further includes receiving a second indication that the mobility device transported the items to the parking lot and placed the items in a vehicle associated with a user of the user device.

Abstract: A system and associated method provides a visualization of a life cycle of a trade order. The visualization may be in the form of a tree structure with a plurality of linked nodes. Each node may be associated with an event that occurs during the life cycle of the trade. A monitoring system receives information associated with a plurality of events associated with the trade order, generates a plurality of nodes based on the received information, stores identifiers associated with each of the plurality of nodes, and links the plurality of nodes based on the identifiers to create the tree structure. The monitoring system also performs a verification process to determine whether the visualization is missing information or includes incorrect information and alerts to a discrepancy identified during the verification process.

Abstract: A network device can place some or all of the packet processing pipeline into a low-power state for detected idle intervals of sufficient duration. The network device detects idleness greater than a critical duration and automatically engages a low-power mode involving clock throttling and/or clock gating. The power savings in the packet processing pipeline in the network device is based on the average long-term residency in idleness. The idle power is reduced for the packet processing pipeline in the network device by detecting average long-term idleness as a function of the minimum latency of the packet processing pipeline, which is used to reduce the clock rate of the packet processing pipeline, thereby resulting in power savings for the network device.

Abstract: A computer-implemented system, platform, computer program product, tool, and/or method for re-running alert reports that includes: identifying an alert report to be rerun; collecting information on the alert report; gathering information on the configuration of a data analytics pipeline that generated the alert report; gathering data used to generate the alert report; recreating a regenerated data analytics pipeline based upon the information gathered on the configuration of the data analytics pipeline that generated the alert report; running the regenerated data analytics pipeline using the gathered data to create a rerun alert report; and optionally comparing the rerun to the original run including optionally generating a visual display of the results including in an aspect creating a side-by-side comparison of the tasks.

Abstract: A computer-implemented system, platform, computer program product, and/or method for optimizing a data analytics suspicious activity detection pipeline that includes identifying a data analytics suspicious activity detection (SAD) pipeline for optimization; inputting desired key performance indicators for the data analytics suspicious activity detection (SAD) pipeline; gathering key performance indicators from previous runs of the data analytics suspicious activity detection (SAD) pipeline; identifying candidate pipeline configurations for simulation runs; running simulations of the candidate pipeline configurations; analyzing the simulations of the candidate pipeline configurations; and identifying the optimal pipeline configuration for the desired key performance indicators.

Abstract: Embodiments relate to a system, program product, and method for automatically executing an impact analysis of a data analytics pipeline to determine impacts to the pipeline subject to changes to input data and the pipeline. The method includes determining, automatically, components of the pipeline that are impacted by the implemented changes. The method also includes identifying datasets to rescore through the pipeline. Each of the datasets to rescore have been scored through the pipeline prior to the changes such that previous scores of each of the respective datasets have been determined by the pipeline prior to the changes. The method further includes rerunning, through only the determined impacted components, the datasets, thereby generating rescores of the datasets. The method also includes retrieving each of the previous scores of the datasets, comparing the rescores with the respective previous scores, and transmitting, subject to the comparing, alerts to an output device.

Abstract: Examples described herein relate to a network interface device that includes circuitry to determine a target time domain in which to translate a time stamp associated with a workload and identify the target time domain to cause translation of the time stamp associated with the workload to the target time domain. In some examples, the network interface device stores time domain translation parameters of time stamps from a first time domain to one or more time domains and the network interface device translates the time stamp from the first time domain to the one or more time domains. In some examples, the network interface device comprises circuitry to store time domain translation parameters of time stamps from a first time domain to one or more time domains and the server is to perform translation of the time stamp from the first time domain to the one or more time domains based on the time domain translation parameters.

Abstract: A processor may receive target data regarding initial targets. The initial targets may relate to specific values for a first set of factors regarding performance of tasks for a first time period. The processor may receive task data regarding the performance of the tasks. The task data may be associated with values for a second set of factors over a second time period. The processor may analyze attributes of the tasks. The processor may generate feature data regarding features of the task. The features may relate to the attributes of the tasks that can be varied to perform the tasks over the second time period. The processor may generate a simulation of the performance of the tasks using the task data and the feature data.

Abstract: In some embodiments, a processor may receive a claim, where the claim relates to an event. The processor may identify characteristics of the claim. The processor may determine, using an AI model, an alert reason based on a similarity of the characteristics of the claim to characteristics of one or more other claims. The processor may generate an alert notification, and the processor may output the alert notification to a user.

Abstract: A computer implemented method and apparatus receive an element of information via a network interface and analyze the element of information. The method further comprises identifying a related entity to a subject of interest (SOI) based on the analyzing. The method further comprises creating a knowledge graph that represents a relationship between the SOI and the related entity, and determining an overall risk score of the SOI that uses the knowledge graph. An alert may be transmitted, via the network interface, based on the overall risk score.

Abstract: A computer-implemented system, method and/or computer program product to monitor changes in business risk of a targeted entity includes retrieving one or more industry classifications for one or more core businesses of the targeted entity; receiving news feeds related to the one or more industry classifications; detecting and extracting negative news related to the core businesses of the targeted entity from the news feeds; calculating an industry confidence score based upon the negative news; determining if the industry confidence score is greater than an industry confidence threshold; calculating, in response to the industry confidence score being larger than the industry confidence threshold, an entity confidence score for the targeted entity based upon negative news; and generating, in response to the entity confidence score being larger than an entity confidence threshold, an alert report for the targeted entity.

Abstract: A computer categorizes a news article by an activity and an associated activity phase, includes receiving, by a computer, at least one news article from an article source. The computer assigns for each news article, an activity of focus selected from a list of target activities, using a first machine learning model. The computer identifies, for each news article, at least one activity phase candidate selected from a list of activity phases associated with the activity of focus, using a second machine learning model. The computer determines, for each of new article, an activity phase of focus from among the activity phase candidates. The determination is based, at least in part on a confirmation attribute associated with the article. The computer categorizes each of the articles by said activity of focus and said activity phase of focus.

Abstract: A computer-implemented system, method and computer program product for preparing alert reports that includes: receiving an override request to override an insight used to prepare the alert reports; determining, determining one or more execution pipelines used to prepare the alert reports that used the insight that is the subject of the override request; determining one or more impacted pipeline runs that were executed to prepare the alert reports that used the insight that is the subject of the override request; updating the one or more execution pipelines used to prepare the alert reports; and generating new alert reports, wherein generating the new alert reports comprises re-running the one or more impacted pipeline runs using the one or more updated execution pipelines wherein the insight that is the subject of the override request is overridden.