Context-Aware Action Suggestion via Application Slice Interface
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Solution Overview
Problem
Current computing devices require users to navigate complexly through multiple applications and menus to access relevant applications for specific tasks, leading to inefficient task completion.
Innovation Solution
A method that analyzes content associated with a window on a user device to identify the task being performed and suggests actions that can be performed via another application, presenting a subset of functionalities through a limited-function user interface called a 'slice' to facilitate task completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users navigate through multiple applications and menus to access relevant applications for specific tasks, then users can access the full functionality of applications, but the complexity of operation increases and time is lost
Solution Approach 1:
The system performs preliminary analysis of the user's current task context (such as analyzing content in the active window) to predict which application the user needs before the user has to manually search for it. This preliminary action eliminates the need for users to navigate through multiple applications and menus, directly resolving the contradiction between ease of operation and time loss.
2Productivity
If users manually navigate through applications and input data, then users can perform tasks, but productivity decreases due to complex navigation steps
Solution Approach 1:
The system provides self-service by automatically analyzing the user's current task context and suggesting the relevant application without requiring manual navigation. The system serves itself by using its own analytical capabilities to assist the user, eliminating the need for complex manual navigation steps and improving productivity.
3Adaptability or versatility
If the system presents all functionalities of an application, then users have complete control, but the user interface becomes complex and overwhelming
Solution Approach 1:
The system applies local quality by presenting only the specific subset of functionalities from the suggested application that are relevant to the user's current task context. Instead of showing all functionalities of an application, the system selectively displays only the necessary controls and options, maintaining both versatility and simplicity.
4Productivity
If users scroll through chronologically arranged windows to find a specific application, then all applications are accessible, but the time required to locate the application increases
Solution Approach 1:
The system introduces an intermediary component that analyzes the user's current task context and acts as a mediator between the user and the applications. This intermediary suggests the relevant application based on contextual analysis, eliminating the need for users to manually scroll through chronologically arranged windows and significantly reducing the time to locate the application.
Data Source
AI summary
This document describes techniques for suggesting actions based on machine learning. These techniques determine a task that a user desires to perform, and presents a user interface through which to perform the task. To determine this task, the techniques can analyze content displayed on the user device or analyze contexts of the user and user device. With this determined task, the techniques determine an action that may assist the user in performing the task. This action is further determined to be performable through analysis of functionalities of an application, which may or may not be executing or installed on the user device. With some subset of the application's functionalities determined, the techniques presents the subset of functionalities via the user interface. By so doing, the techniques enable a user to complete a task more easily, quickly, or using fewer computing resources.