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: Embodiments of the present invention describe creating a mesh network of autonomous vehicles. Embodiments describe, for a set of autonomous vehicles configured to perform joint tasks, creating a plurality of subset networks of autonomous vehicles based on geographical proximity, wherein the plurality of subset networks of autonomous vehicles overlap to form a mesh network of autonomous vehicles, and wherein the mesh network of autonomous vehicles and the subset networks of autonomous vehicles support a non-centralized task assignment feature to assign tasks to autonomous vehicles in the mesh network. Additionally, embodiments describe sending a status signal to a first autonomous vehicle in the mesh network via a second autonomous vehicle in the mesh network, wherein the first autonomous vehicle is in a same subset network of autonomous vehicles as the second autonomous vehicle.

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.

Abstract: A method, system, and computer program product for generating context-based tailored emoticons within a communication scenario are provided. The method receives detects an emotion of a user within a communication stream. A set of candidate emojis are generated. A set of emoticons are generated from the set of candidate emojis and a representation of the user. The set of emoticons are presented to the user in a user interface on a computing device associated with the user. The method incorporates a selected emoticon of the set of emoticons into the communication stream with the selected emoticon being selected by the user from the user interface.

Abstract: Machine learning model training corpus debiasing includes identifying an attribute of input text selected from the training corpus, the attribute including word(s) of the input text, and the attribute corresponding to an attribute class encompassing different possible class values, recognizing bias in the input text with respect to the attribute class, and generating output text corresponding to the attribute and imparting diversity with respect to the attribute class and relative to the input text, where generating the output text uses an optimization function based on loss objectives to minimize loss in the generated output text as compared to the input text.

Abstract: Provided is a method, system, and computer program product for analyzing an electronic health record (EHR) using robotic process automation (RPA). A processor may analyze an EHR associated with a user. The processor may identify, based on analyzing the EHR, one or more health parameters that are outside of a threshold range. The processor may determine a set of recommended actions that may be performed to cause the health parameter to fall within the threshold range. The processor may analyze activity data associated with the user. The processor may identify, based on the activity data, a set of known activities performed by the user. The processor may correlate the recommended actions with the known activities to identify a subset of personalized actions that are specific to the user. The processor may send the subset of personalized actions to the user.

Abstract: Systems, methods, and computer programming products for versioning machine learning models. Changes between new and existing datasets are detected, quantified and compared using statistical and semantic feature comparisons. Recommendations for versioning existing models are in response to detecting changes between the feature importance of datasets used in the application of the machine learning model and new datasets that introduce new features or features that evolve over time in such a manner that feature importance has shifted away from one or more features of the first dataset to the new dataset. Based on the changes in feature importance, statistical changes and semantic feature comparisons, the recommendations provided describe whether models should be updated with a re-trained model, or that the existing features of the model do not indicate a need for re-training.

Abstract: Provided are a computer program product, system, and method for generating constraints based on reported crop arrivals to marketplaces and remote sensed data to estimate farm yields of farm fields. A total arrival quantity constraint for a marketplace is generated comprising a function of a reported arrival of crops at a marketplace and an estimated arrival to the marketplace comprising a sum of farm yields for the farm fields, wherein the farm yields comprise variables to optimize. Sensed data of the farm fields is used to determine relationships of the farm yields for the farm fields. Comparative farm yield constraints are generated comprising relationships of the farm yields for different pairs of farms. A constraint optimization problem is solved based on the total arrival quantity constraint and comparative farm yield constraints to calculate the farm yields of the farm fields.