International business machines corporation (20240289556). ACTIVE COMMUNICATION RECOMMENDATIONS simplified abstract
Contents
ACTIVE COMMUNICATION RECOMMENDATIONS
Organization Name
international business machines corporation
Inventor(s)
TERRI VANESSA Dillon of COSTA MESA CA (US)
JEREMY R. Fox of AUSTIN TX (US)
ANDREW R. Jones of AUSTIN TX (US)
RAGHUVEER PRASAD Nagar of BANGALORE (IN)
ACTIVE COMMUNICATION RECOMMENDATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240289556 titled 'ACTIVE COMMUNICATION RECOMMENDATIONS
Simplified Explanation: The patent application describes a computer-implemented method that identifies active communication between multiple users, determines the context of the communication, searches for historical communications with a similar context, analyzes the historical communications for relevant digital content, and generates a recommendation to use the digital content in the active communication based on the similar context.
Key Features and Innovation:
- Identification of active communication between users
- Determination of communication context
- Search for historical communications with similar context
- Analysis of historical communications for relevant digital content
- Generation of recommendations for using digital content in active communication
Potential Applications: This technology could be applied in social media platforms, messaging apps, online forums, and collaborative work environments to enhance user interactions and content sharing.
Problems Solved: This technology addresses the challenge of finding relevant digital content to enhance ongoing conversations and interactions between users in various online platforms.
Benefits:
- Improved user engagement
- Enhanced content sharing
- More personalized recommendations
- Increased user satisfaction
Commercial Applications: The technology could be utilized by social media companies, messaging app developers, and online collaboration tools to improve user experience, increase user retention, and drive user engagement.
Prior Art: Prior art related to this technology may include research on recommendation systems, content analysis algorithms, and communication context detection methods in the field of computer science and artificial intelligence.
Frequently Updated Research: Researchers in the fields of natural language processing, machine learning, and human-computer interaction may be conducting studies relevant to the advancement of this technology.
Questions about the Technology: 1. How does this technology differentiate between relevant and irrelevant digital content for recommendations? 2. What are the privacy implications of analyzing historical communications for generating recommendations?
Original Abstract Submitted
according to the computer-implemented method, an active communication between multiple users is identified. a context of the active communication is determined. historical communications are searched for a similar context to the context of the active communication. the searched historical communications are analyzed for digital content that is relevant to the context. a recommendation is generated to use the digital content in the active communication based on the similar context.
