18669060. SYSTEMS AND METHODS FOR GENERATING DYNAMIC CONVERSATIONAL RESPONSES THROUGH AGGREGATED OUTPUTS OF MACHINE LEARNING MODELS simplified abstract (Capital One Services, LLC)

From WikiPatents
Revision as of 05:58, 18 October 2024 by Wikipatents (talk | contribs) (Creating a new page)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigation Jump to search

SYSTEMS AND METHODS FOR GENERATING DYNAMIC CONVERSATIONAL RESPONSES THROUGH AGGREGATED OUTPUTS OF MACHINE LEARNING MODELS

Organization Name

Capital One Services, LLC

Inventor(s)

Minh Le of McLean VA (US)

SYSTEMS AND METHODS FOR GENERATING DYNAMIC CONVERSATIONAL RESPONSES THROUGH AGGREGATED OUTPUTS OF MACHINE LEARNING MODELS - A simplified explanation of the abstract

This abstract first appeared for US patent application 18669060 titled 'SYSTEMS AND METHODS FOR GENERATING DYNAMIC CONVERSATIONAL RESPONSES THROUGH AGGREGATED OUTPUTS OF MACHINE LEARNING MODELS

    • Simplified Explanation:**

This patent application describes methods and systems for generating dynamic conversational responses, enhancing interactive exchanges with users through specialized data enrichment methods and machine learning models.

    • Key Features and Innovation:**
  • Specialized methods for enriching data indicative of user intent before processing through machine learning models
  • Specialized architecture for machine learning models that leverage user interface format
    • Potential Applications:**

This technology could be applied in chatbots, virtual assistants, customer service platforms, and interactive voice response systems.

    • Problems Solved:**

This technology addresses the challenge of providing dynamic and contextually relevant conversational responses to users in real-time.

    • Benefits:**
  • Improved user experience in interactive exchanges
  • Enhanced efficiency in processing user intent
  • Personalized and engaging conversational interactions
    • Commercial Applications:**

This technology could be utilized in customer service industries, e-commerce platforms, and any application requiring interactive communication with users.

    • Questions about Dynamic Conversational Responses:**

1. How does this technology improve user engagement in conversational interactions? 2. What are the key advantages of using specialized data enrichment methods in generating dynamic conversational responses?


Original Abstract Submitted

Methods and systems are described herein for generating dynamic conversational responses. For example, dynamic conversational responses may facilitate an interactive exchange with users. Therefore, the methods and systems used specialized methods to enriched data that may be indicative of a user's intent prior to processing that data through the machine learning model, as well as a specialized architecture for the machine learning models that take advantage of the user interface format.