18652785. INTENT PREDICTION FOR DIALOGUE GENERATION simplified abstract (Capital One Services, LLC)

INTENT PREDICTION FOR DIALOGUE GENERATION

Organization Name

Capital One Services, LLC

Inventor(s)

Victor Alvarez Miranda of McLean VA (US)

Rui Zhang of New York NY (US)

Vinay Igure of Ashburn VA (US)

Scott Karp of Washington DC (US)

Erik Mueller of Chevy Chase MD (US)

Tanushree Luke of Alexandria VA (US)

Kunlaya Soiaporn of Falls Church VA (US)

INTENT PREDICTION FOR DIALOGUE GENERATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18652785 titled 'INTENT PREDICTION FOR DIALOGUE GENERATION

Simplified Explanation: This patent application focuses on predicting user intents and generating dialogue in a chat interface based on the user's latest activity information.

Key Features and Innovation:

• Obtaining a chat initiation request from a user
• Providing latest activity information to a prediction model to predict user intents
• Selecting candidate questions matching the predicted intents from a question set
• Simultaneously presenting candidate questions on the chat interface

Potential Applications: This technology can be applied in customer service chatbots, virtual assistants, and online messaging platforms to enhance user interactions.

Problems Solved: This technology addresses the challenge of accurately predicting user intents in real-time conversations and generating relevant dialogue to improve user engagement.

Benefits:

• Improved user experience in chat interactions
• Enhanced efficiency in responding to user queries
• Personalized dialogue generation based on user intents

Commercial Applications: The technology can be utilized in customer service industries, e-commerce platforms, and social media networks to automate responses and provide personalized interactions with users.

Questions about Intent Prediction and Dialogue Generation: 1. How does this technology improve user engagement in chat interfaces? 2. What are the potential challenges in accurately predicting user intents in real-time conversations?

Frequently Updated Research: Stay updated on advancements in natural language processing and machine learning algorithms to enhance the accuracy of intent prediction and dialogue generation in chat interfaces.

Original Abstract Submitted

In certain embodiments, intent prediction and dialogue generation may be facilitated. In some embodiments, a chat initiation request may be obtained from a user. The latest activity information associated with the user may be provided to a prediction model to obtain a first set of predicted intents of the user. For each intent of the first set of predicted intents, a candidate question may be selected from a question set based on the candidate question matching the intent. In some embodiments, the candidate questions may be simultaneously presented on the chat interface.