18611039. ENHANCED LOGITS FOR NATURAL LANGUAGE PROCESSING simplified abstract (ORACLE INTERNATIONAL CORPORATION)

ENHANCED LOGITS FOR NATURAL LANGUAGE PROCESSING

Organization Name

ORACLE INTERNATIONAL CORPORATION

Inventor(s)

Ying Xu of Albion (AU)

Poorya Zaremoodi of Melbourne (AU)

Thanh Tien Vu of Brisbane (AU)

Cong Duy Vu Hoang of Melbourne (AU)

Vladislav Blinov of Melbourne (AU)

Yu-Heng Hong of Carlton (AU)

Yakupitiyage Don Thanuja Samodhye Dharmasiri of Melbourne (AU)

Vishal Vishnoi of Redwood City CA (US)

Elias Luqman Jalaluddin of Seattle WA (US)

Manish Parekh of San Jose CA (US)

Thanh Long Duong of Melbourne (AU)

Mark Edward Johnson of Sydney (AU)

ENHANCED LOGITS FOR NATURAL LANGUAGE PROCESSING - A simplified explanation of the abstract

This abstract first appeared for US patent application 18611039 titled 'ENHANCED LOGITS FOR NATURAL LANGUAGE PROCESSING

Simplified Explanation: The patent application discusses techniques for using enhanced logit values in chatbot systems to classify user utterances.

Key Features and Innovation:

• Chatbot system receives user utterance and inputs it into a machine-learning model with network layers.
• Final network layer includes a logit function to map probabilities for resolvable and unresolvable classes.
• Machine-learning model maps probabilities to logit values for classification of utterances.

Potential Applications: This technology can be applied in various chatbot systems to improve the accuracy of classifying user messages.

Problems Solved: This technology addresses the challenge of accurately classifying user utterances in chatbot systems.

Benefits:

• Enhanced accuracy in classifying user messages.
• Improved user experience with chatbot interactions.

Commercial Applications: Potential commercial applications include customer service chatbots, virtual assistants, and automated messaging systems.

Prior Art: Researchers can explore prior art related to machine-learning models for chatbot systems and natural language processing.

Frequently Updated Research: Stay updated on advancements in machine-learning models for chatbot systems and natural language processing to enhance classification accuracy.

Questions about Enhanced Logit Values in Chatbot Systems: 1. How do enhanced logit values improve the classification of user utterances in chatbot systems? 2. What are the potential implications of using enhanced logit values in chatbot systems for natural language processing?

Original Abstract Submitted

Techniques for using enhanced logit values for classifying utterances and messages input to chatbot systems in natural language processing. A method can include a chatbot system receiving an utterance generated by a user interacting with the chatbot system and inputting the utterance into a machine-learning model including a series of network layers. A final network layer of the series of network layers can include a logit function. The machine-learning model can map a first probability for a resolvable class to a first logit value using the logit function. The machine-learning model can map a second probability for a unresolvable class to an enhanced logit value. The method can also include the chatbot system classifying the utterance as the resolvable class or the unresolvable class based on the first logit value and the enhanced logit value.