Value-Based Action Presentation for Touchscreen Content
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Solution Overview
Problem
Users face cumbersome processes when trying to perform actions related to content on their devices, such as finding and interacting with information about a restaurant, as they need to manually select, copy, and input data, which is particularly cumbersome on touchscreen devices.
Innovation Solution
A computer-implemented method and system that identifies a referent entity from selected content and proposes actions to the user based on the value of these actions, such as estimated time savings, allowing users to select actions that are less commonly chosen but offer significant time benefits, like making a reservation or getting directions, by displaying them in order of their associated value.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually perform actions such as finding, selecting, copying, and inputting data to complete tasks like making a reservation or obtaining directions, then the actions can be completed with basic device functionality, but the process becomes especially cumbersome on touchscreen devices and requires multiple input actions
Solution Approach 1:
The system performs preliminary actions by automatically identifying the referent entity from selected content and pre-computing a list of relevant actions with their associated values. This eliminates the need for users to manually search for and input data, as the system has already prepared the action recommendations before the user needs them.
Solution Approach 2:
The system enables self-service by automatically analyzing the selected content, identifying the referent entity, and generating a personalized list of actions based on the content and user context. The system serves itself by computing the values associated with each action without requiring user input, allowing users to simply select from the presented options.
2Adaptability or versatility
If the system presents all available actions to the user, then the user has complete information to choose from, but the interface becomes complex and overwhelming
Solution Approach 1:
The system applies local quality by differentiating the presentation of actions based on their associated values. High-value actions are prominently displayed with their value indicators, while lower-value actions are either de-emphasized or omitted. This creates a non-uniform interface that adapts to the specific context and user needs rather than presenting all actions equally.
Solution Approach 2:
The system changes the parameter of action presentation by sorting and filtering actions based on their computed values. Instead of presenting actions in a fixed order or alphabetically, the system dynamically reorders them according to their associated values, which are derived from factors such as user preferences, context, and predicted utility. This parameter-based reorganization simplifies the interface by highlighting the most relevant actions.
3Productivity
If the system calculates and presents actions based on their associated values computed from user behavior data, then actions that save significant time can be identified and prioritized, but the system requires complex computation and data processing
Solution Approach 1:
The system performs preliminary computation by pre-calculating the values associated with each potential action based on user behavior data and context. This computation is done in advance, allowing the system to quickly present sorted action recommendations without requiring complex real-time calculations when the user interacts with the content.
Solution Approach 2:
The system introduces an intermediary computational layer that processes user behavior data and transforms it into actionable value metrics. This intermediary layer acts as a mediator between the raw data and the user interface, computing the associated values for each action and filtering out less relevant options before presenting the final sorted list to the user.
Data Source
AI summary
Computer-implemented methods for proposing actions to a user to select based on the value of the actions to the user are provided. In one aspect, a method includes receiving content selected by a user from a device, and identifying a plurality of actions to be executed that are associated with a referent entity identified from the selected content, wherein each action has an associated value to the user. The method also includes providing, for display, an identifier of each of at least a subset of the actions based on their associated values. Systems and machine-readable storage media are also provided.