20240028653. SYSTEMS AND METHODS FOR SELECTING SUPPLEMENTAL CONTENT FOR A USER BASED ON A HELPING USER'S BEHAVIOR simplified abstract (Rovi Guides, Inc.)

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SYSTEMS AND METHODS FOR SELECTING SUPPLEMENTAL CONTENT FOR A USER BASED ON A HELPING USER'S BEHAVIOR

Organization Name

Rovi Guides, Inc.

Inventor(s)

Mona Singh of Cary NC (US)

SYSTEMS AND METHODS FOR SELECTING SUPPLEMENTAL CONTENT FOR A USER BASED ON A HELPING USER'S BEHAVIOR - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240028653 titled 'SYSTEMS AND METHODS FOR SELECTING SUPPLEMENTAL CONTENT FOR A USER BASED ON A HELPING USER'S BEHAVIOR

Simplified Explanation

The patent application describes systems and methods for selecting supplemental content based on a conversation between a user and a helper. The methods analyze the conversation to determine the context and whether the discussed content is associated with a product or service of interest to the user. The application also determines whether to track the helper's behavior and interactions after the conversation. If the helper is tracked, their biometrics, such as gaze and heartbeat, are used to determine their interest in a consumed product or service. Supplemental content related to the helper's interested products is filtered based on user preferences and transmitted to the user. Knowledge trees associated with the supplemental content are provided for user access, including the basis for recommendation, source of knowledge, and other related details.

  • Systems and methods for selecting supplemental content based on a conversation between a user and a helper are disclosed.
  • The methods analyze the conversation to determine the context and whether the discussed content is associated with a product or service of interest to the user.
  • A factor-based determination is made whether to track the helper's behavior and interactions after the conversation.
  • If the helper is tracked, their biometrics, such as gaze and heartbeat, are used to determine their interest in a consumed product or service.
  • Supplemental content related to the helper's interested products is filtered based on user preferences and transmitted to the user.
  • Knowledge trees associated with the supplemental content are provided for user access, including the basis for recommendation, source of knowledge, and other related details.

Potential applications of this technology:

  • Personalized content recommendation systems in various industries such as e-commerce, entertainment, and education.
  • Virtual reality experiences and media consumption platforms that can track user and helper interactions to provide tailored content suggestions.
  • Customer service and support systems that utilize conversation analysis and helper tracking to offer relevant information and assistance.

Problems solved by this technology:

  • Overwhelming amount of content available to users can make it difficult to find relevant and interesting information.
  • Lack of personalized recommendations can result in a poor user experience and reduced engagement.
  • Inefficient customer service interactions where helpers may not have access to relevant knowledge or understanding of user preferences.

Benefits of this technology:

  • Improved user experience by providing personalized and relevant supplemental content based on conversations and user preferences.
  • Increased engagement and satisfaction as users are more likely to find content of interest to them.
  • Enhanced customer service interactions with helpers having access to knowledge trees and understanding user preferences.


Original Abstract Submitted

systems and methods for selecting supplemental content based on a conversation between a user and a helper are disclosed. the methods analyze a conversation, or other interactions, to determine the context and determine whether content discussed is associated with a product or service in the marketplace and of interest to the user. a factor-based determination is made whether to track helper's behavior and interactions after the conversation. when the helper is tracked, based on their tracing preferences, the helper's biometrics, such as gaze and/or heartbeat, are used to determine their interest in a product or service consumed, such as via media consumption, virtual reality experiences, or other online and offline interactions. supplemental content related to helper's interested products are filtered based on user preferences and transmitted to the user. knowledge trees associated with the supplemental content that include the basis for recommendation, source of knowledge, and other knowledge related details are provided for user access.

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