Google llc (20240311697). ACTION SUGGESTIONS FOR USER-SELECTED CONTENT simplified abstract
Contents
ACTION SUGGESTIONS FOR USER-SELECTED CONTENT
Organization Name
Inventor(s)
Matthew Sharifi of Kilchberg (CH)
Daniel Ramage of Seattle WA (US)
David Petrou of Brooklyn NY (US)
ACTION SUGGESTIONS FOR USER-SELECTED CONTENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240311697 titled 'ACTION SUGGESTIONS FOR USER-SELECTED CONTENT
Simplified Explanation: The patent application describes systems and methods for suggesting actions based on selected text displayed on a mobile device.
Key Features and Innovation:
- Converting text selection into a query for action suggestions.
- Training a model to predict actions associated with mobile applications.
- Displaying predicted actions on the mobile device.
- Generating positive training examples from search records for the model.
- Mapping websites to mobile applications for action suggestions.
Potential Applications: This technology can be applied in mobile devices to suggest relevant actions based on selected text, improving user experience and efficiency.
Problems Solved: This technology addresses the challenge of quickly finding and executing relevant actions based on displayed content on mobile devices.
Benefits:
- Enhanced user experience on mobile devices.
- Increased efficiency in performing actions based on displayed content.
- Personalized suggestions for actions based on user behavior.
Commercial Applications: The technology can be utilized in mobile applications, search engines, and digital assistants to provide tailored action suggestions to users, potentially increasing user engagement and satisfaction.
Prior Art: Prior art related to this technology may include research on natural language processing, machine learning models for action prediction, and mobile device interaction design.
Frequently Updated Research: Researchers may be exploring advancements in machine learning algorithms for more accurate action prediction models, as well as user behavior analysis for improved personalized suggestions.
Questions about Action Suggestion Technology: 1. How does this technology improve user interaction with mobile devices? 2. What are the potential privacy concerns associated with using this technology?
Question 1: How does this technology improve user interaction with mobile devices?
Answer 1: This technology enhances user interaction by providing personalized action suggestions based on selected text, making it easier for users to perform relevant tasks quickly.
Question 2: What are the potential privacy concerns associated with using this technology?
Answer 2: Potential privacy concerns may include the collection and analysis of user data to generate personalized action suggestions, raising questions about data security and user consent.
Original Abstract Submitted
systems and methods are provided for suggesting actions for selected text based on content displayed on a mobile device. an example method can include converting a selection made via a display device into a query, providing the query to an action suggestion model that is trained to predict an action given a query, each action being associated with a mobile application, receiving one or more predicted actions, and initiating display of the one or more predicted actions on the display device. another example method can include identifying, from search records, queries where a website is highly ranked, the website being one of a plurality of websites in a mapping of websites to mobile applications. the method can also include generating positive training examples for an action suggestion model from the identified queries, and training the action suggestion model using the positive training examples.
