Abstract: Systems, computer program products, and methods are described herein for implementing auto didactic content generation using reinforcement learning. The present invention is configured to retrieve a user interaction portfolio of a user associated with a completion of a first task; determine requirements associated with the first task; determine an interaction score associated with the user; determine a target interaction score associated with the first task; determine that the interaction score associated with the user is less than the target interaction score; electronically receive, from a knowledge repository, a first video file demonstrating the one or more interaction requirements; generate a modified first video file; and transmit control signals configured to cause a computing device of the user to display the modified first video file to the user.

Abstract: The objective of the present invention is to diversify the types of OS compatible with constituent elements of an HMI program. A support device receives a specification of UI elements of program code compatible with a first OS type, said UI elements constituting an HMI program executed by control devices which are targets of factory automation (FA); generates program code of UI elements compatible with a second OS type from the specified UI elements; and generates a wrapper program, which includes the program code compatible with the second OS type and an instruction code instructing to generate an execution module that includes the relevant program code, when a condition that the OS possessed by the target device is not the first OS type is satisfied. A program in executable code is generated from the HMI program having the wrapper program incorporated therein.

Abstract: Systems and methods provide a recommendation system for recommending sequential content. The training of a reinforcement learning (RL) agent is bootstrapped from passive data. The RL agent of the sequential recommendations system is trained using the passive data over a number of epochs involving interactions between the sequential recommendation system and user devices. At each epoch, available active data from previous epochs is obtained, and transition probabilities are generated from the passive data and at least one parameter derived from the currently available active data. Recommended content is selected based on a current state and the generated transition probabilities, and the active data is updated from the current epoch based on the recommended content and a resulting new state. A clustering approach can also be employed when deriving parameters from active data to balance model expressiveness and data sparsity.

Abstract: One or more computing devices, systems, and/or methods for controlling an output device are provided. For example, features are extracted from data points of an object. A set of data points are identified from the data points based upon the set of data points having features corresponding to target features. Marker elements are assigned to the set of data points. A mapping structure is used to assign output indicators to the marker elements. The output device is controlled to provide output indicators assigned to marker elements as the marker elements become a current focus of the user navigation.

Abstract: A system and methods for facilitation of user interactions with an electronic device. A number of user interface methods are described and may be used alone or in combination with one another to present an enhanced interface to a user. A method of providing user interaction using a compact status indicator is described. A method for providing a virtual scroll wheel to a user for interaction with content sets is described. A method for allowing a user to dynamically modify a scalable user interface is described. A method for providing gesture based input to a user via a virtual gesture pad is described. A method of providing an interactive graphic search query interface is to described. A method for indicating and selecting available content type is described.

Abstract: Methods, systems, and computer storage media for providing action-recommendations (e.g., save action, collaboration action, and upload action) using cloud system operations in a cloud system. For example, action-recommendations are predicted using usage data of applications and communicated to a user (e.g., via a prompt) such that the user elects to perform or not perform the action-recommendation. In operation, usage data for an application and an action-recommendation profile are accessed. Determining that an action-recommendation should be generated is based on the usage data and the action-recommendation profile. The determination is further based on action scores and thresholds (e.g., save action, collaboration action, upload action). When the action scores meet certain thresholds, the action-recommendation is generated as a save-action-recommendation, a collaboration-action-recommendation, or an upload-action-recommendation.

Abstract: There is presented a system for providing a digital multimedia presentation. The system includes a processor and a memory. The system further includes a presentation content database stored in the memory, the presentation content database configured to store a plurality of episodes of a media series each of the plurality of episodes including and a credit portion. The system also includes a media player for execution by the processor and configured to play a selected episode of the plurality of episodes of the media series, and a review and redirection application for execution by the processor and configured to determine a next episode of the selected episode in the media series, where the processor executes the review and redirection pane during or after the credit portion of the selected episode to present a consumer with the next episode of the selected episode in the media series.

Abstract: Methods and systems and mobile device interfaces for creating, joining, organizing and managing via mobile devices affinity groups in a cloud computing environment for social and business purposes.

Abstract: A method includes receiving, via a model building platform, historical user behavior including historical data analysis characteristics; generating, based on the historical data analysis characteristics, a blueprint for guiding user action to accomplish a task, the generating including constructing the blueprint using the historical data analysis characteristics; receiving, via graphical user interface, user input requesting generation of a model and a task description; determining, using the blueprint and based on the task description, data analysis characteristics; and rendering, within the graphical user interface, a prompt to select the determined data analysis characteristics. Related apparatus, systems, techniques and articles are also described.

Abstract: Semantic zoom techniques are described. In one or more implementations, techniques are described that may be utilized by a user to navigate to content of interest. These techniques may also include a variety of different features, such as to support semantic swaps and zooming “in” and “out.” These techniques may also include a variety of different input features, such as to support gestures, cursor-control device, and keyboard inputs. A variety of other features are also supported as further described in the detailed description and figures.

Abstract: A processing device receives three dimensional (3D) motion capture data corresponding to a subject user performing a physical activity and receives attribute data associated with the subject user. The processing device determines a personalized reference data set for the subject user based on 3D motion capture data associated with a group of users performing the physical activity, wherein each user from the group of users shares at least a portion of the first attribute data with the subject user. The processing device provides the personalized reference data set as an input to a trained machine learning model and obtains an output of the trained machine learning model, wherein the output comprises a recommendation for the subject user pertaining to improvement of the physical activity.

Abstract: Methods, systems, and devices supporting adjusting user interfaces based on user usage patterns are described. A page layout server may store an initial page layout for a page corresponding to a data object type, where the initial page layout may be defined by a first user and include a set of user interface components. The page layout server may transmit, to a set of user devices, a first indication of the page for display by the set of user devices according to the initial page layout. The page layout server may track user interactions with the set of user interface components, determine an updated page layout for the page based on an analysis of the tracked user interactions and the initial page layout, and transmit a second indication of the page for display by the set of user devices according to the updated page layout.

Abstract: Implementations are directed to detecting bypass of an authentication system of a web application with actions including receiving one or more webpage logs including web traffic associated with a web application during a defined time period, receiving one or more authentication logs associated with one or more authentication appliances providing authentication services for the web application, determining, based on the one or more webpage logs, one or more webpage log entries corresponding to a user and the defined time period, determining, based on the one or more authentication logs, a total number of correct authentication factors provided by the user during the defined time period, and determining, based on the one or more webpage log entries corresponding to the user and the defined time period and the total number of correct authentication factors provided by the user, that the user bypassed an authentication system of the web application.

Abstract: A XR device and a method for controlling the XR device are discussed. The method includes accessing to a public DB (Database), generating a private DB based on key information of the public DB, where the public DB includes public AR (Artificial Intelligence) information, and the private DB includes private AR information and a whitelist, and acquiring the public AR information or the private AR information.

Abstract: Briefly, embodiments of a system, method, and article for receiving data from one or more clients, where the data indicates user interactions with one or more user interfaces (UIs) of an application. The data may be analyzed with machine learning to identify how users of the one or more clients interact with the UIs of the application. One or more parameters may be generated based, at least in part, on the identification of how the users of the one or more clients interact with the UIs of the application. One or more objects of the application may be modified based, at least in part, on the parameters to reduce user interactions with the one or more UIs.

Abstract: A system and method for early media buffering using prediction of user behavior. In accordance with an embodiment, a user interface displays a plurality of media options from which particular options can be selected. A click determination logic is configured so that a first event associated with a particular option, such as a click event, is passed singly to a media application without trapping for the possibility of a double-click. The media application interprets the first event as a likely selection by a user of the particular option, and uses information associated with the likely selection to begin buffering a corresponding media content. If a second event associated with the particular option is received within a subsequent time interval, then the second event is treated, like a double-click, as confirmation of the user's selection, and the corresponding media content is streamed from its media content buffer.

Abstract: An example operation may include one or more of detecting a web session within an open window of a web browser on a user device, monitoring for user activity on the user device with respect to the web browser, determining there has been a lack of user activity with respect to the web browser for a predetermined amount of time based on the monitoring of the user activity, and temporarily concealing content within the open window of the web browser in response to the lack of user activity.

Abstract: A computing system virtualization continuous authentication system includes a computing system virtualization system that is configured to provide a virtual computing system on a computing client device, and a computing system virtualization management server device that is coupled to the computing system virtualization system and a management terminal. The computing system virtualization management server device monitors user activity information that is associated with a management session that corresponds with the management of the computing system virtualization system and that is associated with an authenticated user account on the computing system virtualization management server device. The computing system virtualization management server device determines that a first authentication challenge is required during the management session based on the user activity information and provides the first authentication challenge to the management terminal.

Abstract: In some embodiments, a computing system identifies a current engagement stage of a user with an online platform by applying a stage prediction model based on interaction data associated with the user. The interaction data describe actions performed by the user with respect to the online platform and context data associated with each of the actions. The computing system further identifies one or more critical events for promoting the user to transition from one engagement stage to a higher engagement stage based on the interaction data associated with the user. The computing system can make the identified current engagement stage of the user or the identified critical event to be accessible by the online platform so that user interfaces presented on the online platform can be modified to improve a likelihood of the user to transit from the current stage to a higher engagement stage.

Abstract: A domain-specific document is retrieved. The domain-specific document is related to the performance of a process in the domain and includes a plurality of document spans and a plurality of annotations that annotate the spans. A goal-based framework is generated from the domain-specific document. The generation is based on the plurality of annotations and based on the plurality of document spans. The goal-based framework includes entities and entity relationships related to performance of the process. The goal-based framework is transformed into a platform agnostic dialog model based on the entities and the entity relationships. At least one platform specific dialog model is provided to at least one automated response system based on the platform agnostic dialog model.