Abstract: A computer-implemented method comprising: sensing, by a personal computing device, a non-verbal communication of a user of the computing device; classifying the non-verbal communication according to at least one attribute of the user; and programming a computer-generated avatar to perform a body movement for an audience viewing the avatar by comparing a determined attribute of the audience and the classified non-verbal communication.

Abstract: First and second sets of sensor data from first and second IoT device sensors are collected. A first set of significant sensor data representing a first event is extracted from the first set of sensor data. A set of terms comprising portions of the first set of significant sensor data is weighted. By analyzing the weighted set of terms, a first set of critical variables describing the first event is identified and added to an ontology. Similarly, a second set of significant sensor data is extracted and a second set of critical variables describing the second event is identified and added to the ontology. Using the ontology, it is determined that the first event is of an event type of the second event. The first sensor and the second sensor are classified to be different variants of a class of sensors that is configurable to sense the event type.

Abstract: In an approach to adjusting notification alerts based on biometric data, one or more computer processors receive one or more user preferences from a first user. One or more computer processors receive a prompt from a computing device to generate a notification. One or more computer processors retrieve biometric data associated with the first user. One or more computer processors determine a biometric state of the first user based on the retrieved biometric data. One or more computer processors adjust a notification alert based on the received one or more user preferences and on the determined biometric state of the first user. One or more computer processors generate the notification alert.

Abstract: A computer enabled method of controlling a secondary system with a primary system for taking commands that includes analyzing a historical database to create a probability factor for matching an initial commands to a primary device and a following interaction to generate secondary requests to a second device. The method further includes receiving a user command at the primary device, and determining whether the user command at the primary device matches at least one initial commands having above a threshold value for the probability factor linking the initial command to the primary device to the request the at least one secondary device. The method further includes sending a signal to activate the at least one secondary device to perform the request without requiring an activation command from the user.

Abstract: A user may be aided in modifying a product that is an assemblage of parts. This aid may involve a processor obtaining images of a target part captured by the user on a mobile device camera. The processor may compare, based on the captured images and a plurality of images of identified parts, the target part to the identified parts. Based on the comparison, the processor may determine an identity of the target part. This aid may also involve a processor obtaining images of a first configuration of a partial assembly of the product captured by a mobile device camera. The processor may compare, based on the captured images, the first configuration to a correct configuration of the partial assembly. Based on the comparison, the processor may determine that the first configuration does not match the correct configuration and may notify the user accordingly.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: preparation of a user profile for a user whose stress response is being managed to attain a goal response. A use mode is determined according to objectives for the goal response. An Augmented Reality (AR) environment customized for the user is generated according to a use mode configuration corresponding to the use mode, and delivered to the user via a user AR device. Responses by the user to the AR environment is monitored by IoT devices, cognitively analyzed, and a determination if the goal response has been attained would be made according to the monitored user response.

Abstract: An augmented-reality system interacts with a physical object that has been embossed or otherwise labeled with one or more bar-code identifiers. The system extracts data from each identifier and uses each element of extracted data to select a computer-generated texture or object. When displaying the augmented-reality environment to a user, the system either replaces the physical object with the computer-generated object or applies the computer-generated texture to a region of a rendered surface of the computer-generated object. The application's selection of computer-generated objects or textures may be modified at any time by a user command, a context-sensitive or environmental factor, an occurrence of a certain virtual event within the augmented-reality environment, or a configuration setting.

Abstract: Methods, systems, and computer program products are provided for monitoring an entity for personal water retention management. Health data for the entity is monitored via one or more sensors. Changes in the monitored health data are tracked over time. Based on the monitored health data, occurrence of a water retention triggering event associated with a provided medical recommendation is determined. When the water retention triggering event is determined to have occurred, the medical recommendation is provided to the entity.

Abstract: In an embodiment, a correlated forecast is computer generated by a processor that receives input data for historic values of a first input variable, creates forecast data for future values of the first input variable using the historic values of the first input variable, generates diagnostic data based on a diagnostic analysis of the forecast data, creates a first diagnostic variable that includes a first diagnostic value from a first cognitive process, generates a feature vector based on a second cognitive process that determines the feature vector by identifying a correlation between the first diagnostic variable and a second diagnostic variable, and generates a final forecast using the feature vector as an input for a cognitive forecasting process, where the first cognitive process determines the first diagnostic value based on the diagnostic data.

Abstract: A system and computer-implemented method are provided for enabling an audio interface enhanced autocorrect feature in a mobile device. The method includes detecting activation of an autocorrect feature of a mobile device in response to a portion of text not appearing in a system dictionary, enabling a microphone in response to activation of the autocorrect feature, receiving audio input from a user responsive to a word replacement by the autocorrect feature, and implementing an enhanced autocorrect action based on the audio input.

Abstract: A computer-implemented method is provided for facilitating an interaction between a first and second entity. The method includes instructing, by a cognitive recommendation engine, a communication aspect of the interaction between the first entity and the second entity. The instructing includes obtaining, by the cognitive recommendation engine, interaction preference data of the first entity related to the communication aspect of the interaction, and based on the interaction preference data, determining by the cognitive recommendation engine, an instruction recommendation. The instruction recommendation facilitates, from the first entity's view, the interaction between the first and second entities. Further, the instructing includes providing by the cognitive recommendation engine the instruction recommendation to the second entity for use by the second entity during the interaction with the first entity.

Abstract: For a first query classification, a query time series is constructed, the query time series comprising a set of natural language queries classified into the first query classification received per unit of time. For a first asset classification, a topic time series is constructed, the topic time series comprising a set of knowledge assets classified into the first asset classification added to a set of knowledge assets per unit of time. From the query time series and the topic time series, a decision tree is generated. By navigating the decision tree, a schedule is generated, the schedule forecasting a time at which a future knowledge asset should be added to the set of knowledge assets in time to answer a future natural language query relative to the knowledge asset.

Abstract: A method and system for using target audience based attributes for modifying an electronic dictionary is provided. The method includes detecting a communication application being enabled via an electronic device. In response, electronic communications of a user are monitored and analyzed with respect to the electronic device and user attributes. Linguistic patterns associated with the electronic communications are determined and with respect to additional electronic communications of said user and a weighted prioritization list of the common terms is generated and electronic dictionary software is modified accordingly. A specified electronic communication currently being entered into the electronic device is monitored and each term of the specified electronic communication is analyzed. In response to the analysis, suggested terms for entering within the specific electronic communication are presented via a graphical user interface of the electronic device.

Abstract: A computer implemented method of controlling the incidence of spoilers in a conversation that includes calculating a baseline of events of interest for participants to a conversation, the calculating of the baseline including machine learning applied to interest indicators for the participants, the interest indicators being derived from data collected from social media accounts of the participants and calendars of the participants in response the participant granting permission for the data collection. The method further includes monitoring of real time conversation between the parties for keywords indicative of a topic of the real time conversation, wherein a spoiler message is predicted when the keywords substantially match the baseline for the events of interest. The method may further include sending an anti-spoiler signal to the participants of the conversation when the keywords substantially match the baseline for the events of interest.

Abstract: A method, computer program product, and a system where a processor(s) of a computing device identifies at least two displays coupled to the processor(s) to render visual objects to a user of the computing device, like a cursor, and processor(s) obtains instructions to render the cursor in various locations on the displays via an input device. The processor(s) obtain a display layout for the displays and resolutions of displays and generates an initial virtual desktop that includes physical real estate of the displays where the processor(s) renders visual objects. The processor(s) determines boundaries of each display and selects outermost two dimensional boundaries of the initial virtual desktops and updates the initial virtual desktop to an area bounded by a virtual rectangle comprising the outermost boundaries, which includes the displays and physical space not useable by the processor(s) to render visual objects.

Abstract: An embodiment of the invention may include a method, computer program product and computer system for image classification and masking. The method, computer program product and computer system may include computing device which may receive image data from one or more sources. The computing device may classify the image data utilizing visual recognition classification and identify one or more classified features, each classified feature being associated with one or more attributes. The computing device may analyze the classified image data to determine if one or more of images of the classified image data contains one or more sensitive attributes. In response to determining one or more images of the classified image data contains one or more sensitive attributes, the computing device may apply a masking technique and may generate one or more masked images.

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: obtaining vocal utterance data representing vocal utterances of multiple users within a venue; processing the vocal utterance data to return metadata associated to the vocal utterance data; predicting using the metadata an item for acquisition by one or more user of the multiple users; and returning an action decision in dependence on the predicting.

Abstract: The present disclosure includes analyzing a voice command or request from a user, received at an Artificial Intelligence (AI) system, for identifying a possibly incorrect or misunderstood voice command or request. A first user is identified and associated to a first user profile, in response to receiving an audio input, including a question or command, at an AI system. A possible defect or error is identified, in whole or in part, of the question or the command, based on the first profile of the first user and a knowledge corpus. A response by the AI system is determined based on the analysis of the content and the user profile for the first user. A possible alternative content is generated, in whole or in part, for the question or the command, and communicated the response including the possible alternative content to the first user.

Abstract: In an approach to training image classification models through the creation and utilization of stub images, one or more computer processors tag ground truth data utilizing subject matter expert inputs for a classification. The one or more computer processors extract one or more features and one or more boundaries from the tagged ground truth data. The one or more computer processors tag the one or more extracted features and the one or more extracted boundaries. The one or more computer processors generate one or more stub images by incorporating the one or more tagged features, and the one or more tagged boundaries at a confidence level. The one or more computer processors train a classification model utilizing the one or more generated stub images. The one or more computer processors deploy the trained classification model.

Abstract: In an approach to optimized interactive communications timing from computing devices, a set of system defaults is received. A verbal communications for an intended recipient is received. An activity data for the intended recipient is received. A criticality score of the verbal communication is determined based on the set of system defaults. An availability score for the intended recipient is determined based on the set of system defaults and the activity data. An optimal time to initiate verbal communications with the intended recipient is determined wherein the optimal time to initiate verbal communications occurs when the criticality score exceeds the availability score. The verbal communication for the intended recipient is initiated at the optimal time.