Abstract: In an approach to meeting summarization for disconnected participants, one or more computer processors detect a start of a collaborative meeting. One or more computer processors monitor a connection to the collaborative meeting of each of one or more participants. One or more computer processors determine a first participant of the one or more participants has disconnected from the collaborative meeting. One or more computer processors record the collaborative meeting. One or more computer processors determine the first participant has re-connected with the collaborative meeting. One or more computer processors synthesize, a first summary of a portion of the collaborative meeting missed by the first participant. One or more computer processors to synthesize, a second summary of a portion of the collaborative meeting recorded after the first participant re-connected with the collaborative meeting. One or more computer processors present the first summary and the second summary to the first participant.

Abstract: A method, a structure, and a computer system for playback optimization. The exemplary embodiments may include transcribing an audio stream at normal and at high playback speed, as well as determining whether portions of the audio stream are unintelligible at the high playback speed. The exemplary embodiments may further include reducing a speed of the high playback speed for portions determined unintelligible, and transcribing the audio stream with the unintelligible portions played at the reduced high playback speed. The exemplary embodiments may further include determining whether the unintelligible portions are still unintelligible at the reduced high playback speed and, if not, identifying the reduced high playback speed as an optimal playback speed of the unintelligible portions. The exemplary embodiments may additionally include, in response to receiving a request to play the audio stream at the high playback speed, playing the unintelligible portions at the optimal playback speed.

Abstract: Disclosed are techniques for automatically identifying significant events. During a training phase, a method can include: training a neural network (NN) to automatically identify significant events, the training including: receiving training data including labeled weather event data for a group of locations over a group of time periods, generating, by the NN, a probability factor representing a chance that a weather event in the training data will be significant for at least one location amongst the locations, and comparing the probability to the received labels, and during a runtime phase: receiving data from sensors, each sensor generating weather event data about a respective location(s), providing the weather event data as inputs to the NN, receiving, as output from the NN, weather event data having a respective significance level greater than a respective predetermined threshold value, and correlating weather events with the outputted weather event data.

Abstract: Processing within a computing environment is facilitated by obtaining a parameterization for a parallelized file system operation of a file system of the computing environment, and executing, and determining performance of, the parallelized file system operation with the parameterization. The process further includes using machine learning to adjust one or more parameters of the parameterization based on performance of the parallelized file system operation to obtain a tuned parameterization, and executing the parallelized file system operation with the tuned parameterization, where the adjusting of one or more parameters of the parameterization enhances performance of the parallelized file system operation within the computing environment.

Abstract: A method includes: receiving, by a processor set, a cloud architecture document; converting, by the processor set, the cloud architecture document to a graph including nodes; determining, by the processor set, cloud environment information for the nodes by analyzing textual content of the nodes using natural language processing; determining, by the processor set, additional cloud environment information for the nodes using domain ontology data; and creating, by the processor set, an Infrastructure as Code (IaC) document based on the cloud environment information and the additional cloud environment information.

Abstract: A method, system, and computer program product for identifying reference data values in a source data set. The method may include inputting a block of attribute values to a predefined machine learning model. The method may also include receiving an indication of a presentation layout of the block of the attribute values and an associated reference data extraction method. The method may also include determining a reading direction of the block of values. The method may also include identifying one or more inspection areas in the reading direction of the block of values. The method may also include determining sets of the one or more inspection areas that share a common presentation feature. The method may also include identifying tokens in an inspection area. The method may also include determining if the inspection area includes reference data values. The method may also include outputting the reference data values.

Abstract: In an approach for routing a user analytic request to a registry of analytics models and data sources and operationalizing the user analytic request, a processor receives a user analytic request. A processor applies natural language processing to the user analytic request. A processor associates a first set of vectors and a second set of vectors from the user analytic request to one or more analytics models and data sources by utilizing a plurality of domain-specific ontologies and a plurality of knowledge bases. A processor performs a semantic search for one or more concepts in the one or more analytics models and data sources. A processor receives the one or more concepts found in the one or more analytics models and data sources. A processor selects an analytics model to process the user analytic request. A processor executes the analytics model. A processor outputs a result to the user.

Abstract: Communications are managed and prioritized by a machine learning process in a vehicle with automated driver assistance. It is detected that the vehicle is currently being operated in manual mode by a human driver. It is detected that a telecommunication device located within the vehicle is receiving a communication. The communication is classified according to a priority. The communication is acted upon based on the priority classification. The driver state is assessed at the conclusion of the communication. The vehicle returns to the manual driving mode if the driver state is compatible with the manual driving mode.

Abstract: A computer-based method, system, and computer program product for automatically identifying significant events for food traceability. The method may comprise receiving a series of events from an agriculture supply chain entity, automatically determining, at a machine learning model of an event analysis module, one or more events in the series having a significance for food traceability greater than a threshold, and automatically reporting the one or more events to a ledger.

Abstract: A method, computer system, and a computer program for group-based authentication are provided. The method may include evaluating each individual of a group for qualification for task to acquire an aggregate skill score associated with the group. The method may further include determining the aggregate skill score exceeds a group task authentication threshold based on the evaluation and granting the group authorization associated with the task responsive to the determination.

Abstract: Embodiments relate to a system, program product, and method for leveraging cognitive systems to facilitate the bilateral contextual alignment of textual material and associated diagrammatic matter. The system, computer program product, and method disclosed herein facilitate leveraging a trained cognitive system to understand textual and diagrammatic patterns established by a user, and to learn to draft and edit such textual material and associated diagrammatic matter based on user behavior and preferences. The cognitive system is trained to bilaterally translate between textual material and diagrammatic matter, where the cognitive system includes natural language processing (NLP) features, diagram analytics features, and one or more user profiles.

Abstract: In a method for intelligently executing predictive simulator, a processor may input a previous input vector of conditions for a predictive simulator collected at a first time into a machine-learning (ML) model. A processor may input a current input vector of conditions for the predictive simulator collected at a second time into the ML model. A processor may determine using the ML model, a binary similarity index. The binary similarity index represents a prediction of similarity between a first output from the predictive simulator based on the previous input and a second output from the predictive simulator based on the current input.

Abstract: A method, a computer program product, and a computer system determine a customized augmented reality workout based on a cognitive state of a user. The method includes determining a current cognitive score of the user based on physical descriptions. The method includes determining the cognitive state of the user based on the current cognitive score. The cognitive state is indicative of a stress level being experienced by the user. The method includes determining the customized augmented reality workout from a plurality of augmented reality workouts based on the cognitive state of the user. The method includes generating the customized augmented reality workout to include at least one virtual component and incorporating at least one feature of real world surroundings. The method includes presenting the customized augmented reality workout to the user via an augmented reality device worn by the user.

Abstract: In an approach to meeting summarization for disconnected participants, one or more computer processors detect a start of a collaborative meeting. One or more computer processors monitor a connection to the collaborative meeting of each of one or more participants. One or more computer processors determine a first participant of the one or more participants has disconnected from the collaborative meeting. One or more computer processors record the collaborative meeting. One or more computer processors determine the first participant has re-connected with the collaborative meeting. One or more computer processors synthesize, a first summary of a portion of the collaborative meeting missed by the first participant. One or more computer processors to synthesize, a second summary of a portion of the collaborative meeting recorded after the first participant re-connected with the collaborative meeting. One or more computer processors present the first summary and the second summary to the first participant.

Abstract: In an approach for enabling a user to visualize a transcript of a discussion via a head-mounted AR device and to selectively copy one or more parts of the transcript that is contextually relevant for inclusion in a new document file or a previously created document file, a processor captures audio of a spoken content of a first participant of a discussion via an AR device worn by a user. A processor analyzes the audio of the spoken content of the first participant. A processor converts the audio of the spoken content of the first participant to text to create a transcript. A processor creates a visualization of the transcript. A processor presents the visualization of the transcript to the user via the AR device. A processor enables the user to copy one or more parts of the transcript into a document file via a selection support.

Abstract: A method for protecting content of online conversational content. The method provides for scanning content of an online conversational exchange between a first device and a second device. A sensitive object included in the content of the online conversation exchange is identified, based on object type information accessible from a protection policy included in respective user profiles. A pseudonymized-object-holder is assigned to the identified sensitive object according to the protection policy of the respective user profiles, and the identified sensitive object identified in the content of the online conversation exchange and stored on both the first device and the second device is replaced with a pseudonymized-object-holder, based on the sensitive-object protection policy of the respective user profiles.

Abstract: A method, computer system, and a computer program product for problem solving using selected datasets from an internet-of-things system are provided. A trigger device in an internet-of-things system may be designated. The internet-of-things system may include the trigger device and internet-of-things devices. A trigger message may be received from the trigger device. A problem may be determined based on the trigger message. Data transmissions may be requested from the internet-of-things devices. Data may be received via the data transmission. The data transmission may be ended. A problem contributor may be identified by inputting the received data and the determined problem into a machine learning model. A problem response for responding to the problem may be generated. The generating may include inputting the problem contributor to the machine learning model. The problem response may be performed.

Abstract: A processor may receive internet data information associated with a user and one or more internet activities performed on one or more devices. The one or more devices may be associated with a surrounding area. The processor may analyze internet data information. The processor may generate an internet data consumption plan. The internet data consumption plan may include one or more recommendations that optimize internet data consumption associated with the one or more internet activities. The processor may dynamically switch at least one of the one or more internet activities between an initial mode and one or more alternative modes. Dynamically switching between the initial mode and the one or more alternative modes is based on the internet data consumption plan.

Abstract: Methods, systems, and computer program products for training an artificial intelligence (AI) of a voice response system. Aspects include receiving, by the voice response system from a user, a voice command to perform a requested action and interpreting, by an AI model, the voice command. Aspects also include performing an action based on the interpretation of the voice command and receiving non-verbal feedback from the user. Aspects further include updating the AI model based on a determination that the non-verbal feedback indicates that the user is not satisfied with the action performed.

Abstract: Cognitive pre-loading of referenced content in electronic mail (e-mail) messages includes determining, using computer hardware, metadata for an electronic message directed to a user, detecting, using the computer hardware, a universal resource locator (URL) within a body portion of the electronic message, determining, using the computer hardware, a content type for the URL, and performing, using the computer hardware, natural language processing on the electronic message to determine an action importance corresponding to the URL. At least a portion of content specified by the URL can be pre-fetched from a data processing system based on the metadata, the content type of the URL, and the action importance. The electronic message and at least a portion of the content can be provided to a client device of the user.