18582513. PERSONALITY REPLY FOR DIGITAL CONTENT simplified abstract (Google LLC)
Contents
PERSONALITY REPLY FOR DIGITAL CONTENT
Organization Name
Inventor(s)
Goekhan Hasan Bakir of Zurich (CH)
Bianca Madalina Buisman of Kilchberg (CH)
PERSONALITY REPLY FOR DIGITAL CONTENT - A simplified explanation of the abstract
This abstract first appeared for US patent application 18582513 titled 'PERSONALITY REPLY FOR DIGITAL CONTENT
The abstract describes a computer-implemented method where a computing system receives digital content from a user device, generates labels indicating attributes of the content, generates conversational replies based on these labels, selects a reply, and outputs it to the user device.
- The method involves receiving digital content, generating labels for its attributes, creating conversational replies based on these labels, selecting a reply, and providing it to the user device.
- This process aims to enhance user interaction with digital content by providing relevant and engaging conversational responses.
- The technology leverages machine learning and natural language processing to analyze content and generate appropriate replies.
- By automating the generation of conversational replies, the method streamlines communication and improves user experience.
- The system's ability to select the most suitable reply from multiple options enhances the quality of interactions between users and digital content.
Potential Applications: - Customer service chatbots - Social media platforms - Content recommendation systems
Problems Solved: - Enhancing user engagement with digital content - Improving the efficiency of communication between users and systems
Benefits: - Personalized and relevant responses to user queries - Streamlined communication processes - Enhanced user experience and satisfaction
Commercial Applications: Title: "Enhancing User Engagement with Automated Conversational Replies" This technology can be utilized in customer service applications, social media platforms, and content recommendation systems to improve user interactions and overall user experience. It has the potential to increase user engagement, satisfaction, and retention rates in various digital platforms.
Prior Art: Researchers can explore existing technologies in the fields of natural language processing, machine learning, and conversational AI to understand the evolution of automated conversational systems.
Frequently Updated Research: Stay updated on advancements in natural language processing, machine learning algorithms, and conversational AI technologies to enhance the capabilities of automated conversational systems.
Questions about the technology: 1. How does this technology improve user engagement with digital content? 2. What are the key components of the system that enable the generation of conversational replies?
Original Abstract Submitted
A computer-implemented method is described. The method includes a computing system receiving an item of digital content from a user device. The computing system generates one or more labels that indicate attributes of the item of digital content. The computing system also generates one or more conversational replies to the item of digital content based on the one or more labels that indicate attributes of the item of digital content. The method also includes the computing system selecting a conversational reply from among the one or more conversational replies and providing the conversational reply for output to the user device.
