Patent classifications
G06F3/0483
DISPLAY CONTROL METHOD AND SYSTEM, MOBILE TERMINAL, AND STORAGE MEDIUM
A display control method and system, a mobile terminal, and a storage medium are provided. The method includes: acquiring a trigger event, the trigger event including at least one of: an event generated by triggering a first display interface or an event generated by triggering a second display interface; acquiring a target display area corresponding to the trigger event; reporting the trigger event to a desktop launcher corresponding to the target display area, so that the desktop launcher starts an interface corresponding to the trigger event in the target display area.
DISPLAY CONTROL METHOD AND SYSTEM, MOBILE TERMINAL, AND STORAGE MEDIUM
A display control method and system, a mobile terminal, and a storage medium are provided. The method includes: acquiring a trigger event, the trigger event including at least one of: an event generated by triggering a first display interface or an event generated by triggering a second display interface; acquiring a target display area corresponding to the trigger event; reporting the trigger event to a desktop launcher corresponding to the target display area, so that the desktop launcher starts an interface corresponding to the trigger event in the target display area.
ELECTRONIC DEVICE WITH VARIABLE DISPLAY AREA AND OPERATION METHOD THEREOF
According to an example embodiment, an electronic device outputs, on a second display screen, a page layout output on a first display screen along with another page layout grouped together with the page layout in response to a screen switch from the first display screen to the second display screen having a greater display area than a display area of the first display screen, and switches the grouped page layouts in response to a swipe input being detected.
Electronic device and control method thereof
An electronic device and method are disclosed. The electronic device includes a foldable display that is at least partially foldable, at least one processor, and at least one memory. The processor implements the method, including detecting, by at least one processor, that a foldable display of the electronic device changes from an unfolded state to a partially folded state, configuring a first region of the foldable display to accept touch inputs in the partially folded state, and configuring a second region of the foldable display to accept non-touch inputs in the partially folded state.
Self-training machine-learning system for generating and providing action recommendations
A user computing entity executes application program code to cause display of an IUI via a user interface of the user computing entity. The IUI comprises an action list comprising one or more action items corresponding to one or more team members of a team. The action items are automatically ordered based on one or more action priorities. At least one of the action items corresponds to a coaching opportunity and a recommendation for responding thereto. The coaching opportunity is automatically identified using a recommendation model trained using machine learning based at least in part on performance data corresponding to a plurality of key performance indicator metrics. The recommendation for responding to the coaching opportunity is determined using the recommendation model and based on the performance data. The recommendation model is trained using information regarding previous handlings of coaching opportunities and corresponding outcome indicators for a cluster of teams.
Self-training machine-learning system for generating and providing action recommendations
A user computing entity executes application program code to cause display of an IUI via a user interface of the user computing entity. The IUI comprises an action list comprising one or more action items corresponding to one or more team members of a team. The action items are automatically ordered based on one or more action priorities. At least one of the action items corresponds to a coaching opportunity and a recommendation for responding thereto. The coaching opportunity is automatically identified using a recommendation model trained using machine learning based at least in part on performance data corresponding to a plurality of key performance indicator metrics. The recommendation for responding to the coaching opportunity is determined using the recommendation model and based on the performance data. The recommendation model is trained using information regarding previous handlings of coaching opportunities and corresponding outcome indicators for a cluster of teams.
Tab visibility
According to one general aspect, a computing device may include an application configured to create a tab in a context of a window, and a window manager configured to register the tab with a first UI element registry. The window manager may be configured to receive, over a network, at least a portion of a second UI element registry from a secondary window manager of a secondary computing device. The portion of the second UI element registry may identify a remote tab previously registered with the secondary window manager. The window manager may be configured to cause a display to provide a graphical arrangement of the tab and the remote tab.
Tab visibility
According to one general aspect, a computing device may include an application configured to create a tab in a context of a window, and a window manager configured to register the tab with a first UI element registry. The window manager may be configured to receive, over a network, at least a portion of a second UI element registry from a secondary window manager of a secondary computing device. The portion of the second UI element registry may identify a remote tab previously registered with the secondary window manager. The window manager may be configured to cause a display to provide a graphical arrangement of the tab and the remote tab.
Invoking an automatic process in a web-based target system using a chat-bot
A method, apparatus and product for chat-based application interface for automation. Using a natural language interface, receiving user input. Based on the user input, determining an automation process of a computer program having a user interface (UI), to be executed. The automation process is executed by utilizing the UI to input data thereto or execute functionality thereof. Additionally or alternatively, a conversation to be implemented by a natural language interface may be defined. The conversation is configured to obtain from the user one or more values corresponding to one or more parameters. The conversation is associated with a parameterized automation process depending on the one or more parameters. The parameterized automation process is invoked automatically by a natural language interface and using one or more values provided by the user to the natural language interface for the one or more parameters.
Invoking an automatic process in a web-based target system using a chat-bot
A method, apparatus and product for chat-based application interface for automation. Using a natural language interface, receiving user input. Based on the user input, determining an automation process of a computer program having a user interface (UI), to be executed. The automation process is executed by utilizing the UI to input data thereto or execute functionality thereof. Additionally or alternatively, a conversation to be implemented by a natural language interface may be defined. The conversation is configured to obtain from the user one or more values corresponding to one or more parameters. The conversation is associated with a parameterized automation process depending on the one or more parameters. The parameterized automation process is invoked automatically by a natural language interface and using one or more values provided by the user to the natural language interface for the one or more parameters.