Abstract: A method includes: hosting, by a computing device, a videoconference among plural users; receiving, by the computing device, input from a sharing user of the plural users, wherein the input initiates a screenshare in the videoconference; creating, by the computing device, document twins of a document shown in the screenshare; and providing, by the computing device and to other users of the plural users, access to respective ones of the document twins in an interface of the videoconference; wherein each of the other users may scroll within a respective one of the document twins independently of other ones of the other users and independently of the screenshare.

Abstract: Classification and visualization of user interactions with an interactive computing platform is provided by building and providing a graphical user interface (GUI) of graphical elements for display on a display device. The graphical elements present visualizations of user interactions between users and an interactive computing platform in progression of the users through tasks based on the user interactions. The graphical elements also present identified features of the user interactions relative to the tasks and progression of the users therethrough. The building and providing includes building and providing, for a task of the tasks, a task element with first features corresponding to subtasks of the task and second features providing relations between the first features.

Abstract: Personalizing sensory feedback based on user sensitivity analysis includes maintaining user-specific parameters for provision of sensory feedback to a user in extended reality. The user-specific parameters apply to specific contextual situations and dictate levels of sensory feedback to provide via stimulus device(s) in the specific contextual situations. Based on an ascertained contextual situation of the user interacting in a target extended reality environment, a set of sensory feedback level parameters is selected for provision of sensory feedback to the user in the target extended reality environment, and stimulus device(s) in the target extended reality environment is/are automatically controlled in the provision of the sensory feedback to the user based on one or more of the selected parameters. The automatically controlling includes electronically communicating with the stimulus device(s) to control at least one stimuli provided to the user by the stimulus device(s).

Abstract: A computer-implemented method, including: receiving, by a computing device, a post referring to a multimedia content; identifying, by the computing device, a time in the post; generating, by the computing device, a validity score based on analyzing contextual data of the time in the post; determining, by the computing device, a correlation between the time in the post to the multimedia content based on the validity score; and publishing, by the computing device, the post with an interactive link to a corresponding time of the multimedia content based on the determined correlation.

Abstract: A system includes: a platform; a payload extending from a platform; an adjustable tether connecting the payload to the platform; and a sail extending from the payload. The system further includes a computer program that is executable to relocate the platform to the area of interest based on a threshold based decision which may include providing a tether and sail configuration.

Abstract: A computer-implemented method, including: receiving, by a computing device, a post referring to a multimedia content; identifying, by the computing device, a time in the post; generating, by the computing device, a validity score based on analyzing contextual data of the time in the post; determining, by the computing device, a correlation between the time in the post to the multimedia content based on the validity score; and publishing, by the computing device, the post with an interactive link to a corresponding time of the multimedia content based on the determined correlation.

Abstract: Classification and visualization of user interactions with an interactive computing platform is provided by building and providing a graphical user interface (GUI) of graphical elements for display on a display device. The graphical elements present visualizations of user interactions between users and an interactive computing platform in progression of the users through tasks based on the user interactions. The graphical elements also present identified features of the user interactions relative to the tasks and progression of the users therethrough. The building and providing includes building and providing, for a task of the tasks, a task element with first features corresponding to subtasks of the task and second features providing relations between the first features.

Abstract: A method includes: hosting, by a computing device, a videoconference among plural users; receiving, by the computing device, input from a sharing user of the plural users, wherein the input initiates a screenshare in the videoconference; creating, by the computing device, document twins of a document shown in the screenshare; and providing, by the computing device and to other users of the plural users, access to respective ones of the document twins in an interface of the videoconference; wherein each of the other users may scroll within a respective one of the document twins independently of other ones of the other users and independently of the screenshare.

Abstract: Classification and visualization of user interactions with an interactive computing platform is provided by building and providing a graphical user interface (GUI) of graphical elements for display on a display device. The graphical elements present (i) visualizations of user interactions between users and an interactive computing platform in progression of the users through tasks based on the user interactions and (ii) identified features of the user interactions relative to the tasks and progression of the users therethrough. The building and providing includes, for each of the tasks, building and providing a respective task element that reflects identified features of a set of user interactions of one or more users in progressing through that task. Building a task element for a task includes building the task element as a polygon having vertices corresponding to subtasks of the task and edges between the vertices.

Abstract: Personalizing sensory feedback based on user sensitivity analysis includes maintaining user-specific parameters for provision of sensory feedback to a user in extended reality. The user-specific parameters apply to specific contextual situations and dictate levels of sensory feedback to provide via stimulus device(s) in the specific contextual situations. Based on an ascertained contextual situation of the user interacting in a target extended reality environment, a set of sensory feedback level parameters is selected for provision of sensory feedback to the user in the target extended reality environment, and stimulus device(s) in the target extended reality environment is/are automatically controlled in the provision of the sensory feedback to the user based on one or more of the selected parameters. The automatically controlling includes electronically communicating with the stimulus device(s) to control at least one stimuli provided to the user by the stimulus device(s).

Abstract: Methods, computer program products, and systems are presented. The method computer program products, and systems can include, for instance: obtaining clothing article data stream data from one or more internet of things (IoT) device disposed in a computing environment, wherein the computing environment is collocated with a residence of a user, the clothing article data stream data representing one or more clothing article of the user; examining data of the clothing article data stream data to determine at least one clothing article parameter value of the one or more clothing article; in dependence at least one clothing article parameter value of the one or more clothing article, and providing user profile data that specifies predicted behavior of the user.

Abstract: An embodiment includes analyzing a first digital image using a first trained neural network that classifies the first image as having a first context based on a plurality of characteristics of the first image. The embodiment generates a data structure that associates first and second elements depicted in the first image based on an affinity detected between the first and second elements in the first context. The embodiment executes a querying process that searches for information requested by a user, and detects that a search result from the querying process conveys a second context that is different from the first context. The embodiment identifies a third element in the data structure having an affinity with the first element in the second context. The embodiment renders a machine-generated image that is generated using a second trained neural network and depicts the first element and the third element in the second context.

Abstract: Debris signature-based robotic cleaning device navigation includes operating the robotic cleaning device in a first mode as part of a vacuum cycle, the device including suction ports configurable for different suction power levels and each port having a suction path along which debris entering through the suction port is collected by the device. In the first operating mode the suction ports are operated at a first suction power level. The navigation also includes changing operation of the device to a second mode and in which the suction ports are operated at a greater suction power, measuring a respective amount of debris collected through each suction port, and selecting a direction in which to navigate the robotic cleaning device based on the debris measurements.

Abstract: Classification and visualization of user interactions with an interactive computing platform is provided by building and providing a graphical user interface (GUI) of graphical elements for display on a display device. The graphical elements present (i) visualizations of user interactions between users and an interactive computing platform in progression of the users through tasks based on the user interactions and (ii) identified features of the user interactions relative to the tasks and progression of the users therethrough. The building and providing includes, for each of the tasks, building and providing a respective task element that reflects identified features of a set of user interactions of one or more users in progressing through that task. Building a task element for a task includes building the task element as a polygon having vertices corresponding to subtasks of the task and edges between the vertices.

Abstract: Classification and visualization of user interactions with an interactive computing platform is provided by applying machine learning (ML) model(s) to user transcripts, the ML model(s) trained to classify interactions with an interactive computing platform, the user transcripts including user interactions between users and the interactive computing platform in progression of the users through tasks based on the user interactions, where the applying classifies the user interactions and identifies features of the user interactions, and building and providing a graphical user interface (GUI) of graphical elements for display on a display device, the graphical elements presenting visualizations of the user interactions and the identified features thereof relative to the tasks and progression of the users therethrough, the GUI including, for each of the tasks, a respective task element that reflects identified features of a set of user interactions of user(s) in progressing through that task.

Abstract: Secure data analytics is provided via a process that identifies sensitive data fields of an initial dataset and mappings between the sensitive data fields and other data fields of the dataset, where analytics processing is to be performed on the initial dataset, then, based on an expectation of data fields, of the initial data set, to be used in performance of the analytics processing and on the identified sensitive data fields, selects and applies a masking method to the initial dataset to mask the sensitive data fields and produce a masked dataset, provides the masked dataset to an analytics provider with a request for the analytics processing, and receives, in response, a generated analytics function, generated based on the masked dataset, that is configured to perform the analytics processing, and invokes the generated analytics function against the initial dataset to perform the analytics processing on the initial dataset.