View source for 18199480. SYSTEM AND METHOD FOR INCORPORATING RISK RELATED TOPICS INTO CHATBOT FUNCTIONALITY simplified abstract (Capital One Services, LLC)

=SYSTEM AND METHOD FOR INCORPORATING RISK RELATED TOPICS INTO CHATBOT FUNCTIONALITY=


==Organization Name==

[[:Category:Capital One Services, LLC|Capital One Services, LLC]]


[[Category:Capital One Services, LLC]]

==Inventor(s)==

[[:Category:Jennifer Kwok of Brooklyn NY (US)|Jennifer Kwok of Brooklyn NY (US)]][[Category:Jennifer Kwok of Brooklyn NY (US)]]

[[:Category:Casey Han of New York NY (US)|Casey Han of New York NY (US)]][[Category:Casey Han of New York NY (US)]]

[[:Category:Daniel E. Miller of Brooklyn NY (US)|Daniel E. Miller of Brooklyn NY (US)]][[Category:Daniel E. Miller of Brooklyn NY (US)]]

[[:Category:Dan Lin of Arlington VA (US)|Dan Lin of Arlington VA (US)]][[Category:Dan Lin of Arlington VA (US)]]

[[:Category:Esther Uhri Cho of Hoboken NJ (US)|Esther Uhri Cho of Hoboken NJ (US)]][[Category:Esther Uhri Cho of Hoboken NJ (US)]]

[[:Category:Alexander Mireles of Clifton VA (US)|Alexander Mireles of Clifton VA (US)]][[Category:Alexander Mireles of Clifton VA (US)]]

[[:Category:Phoebe Atkins of Midlothian VA (US)|Phoebe Atkins of Midlothian VA (US)]][[Category:Phoebe Atkins of Midlothian VA (US)]]

==SYSTEM AND METHOD FOR INCORPORATING RISK RELATED TOPICS INTO CHATBOT FUNCTIONALITY - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18199480 titled 'SYSTEM AND METHOD FOR INCORPORATING RISK RELATED TOPICS INTO CHATBOT FUNCTIONALITY

==Simplified Explanation==

The patent application describes a system and method that utilize a chatbot to provide answers to user inquiries regarding risk-related topics. The system employs natural language processing to determine the intent of the inquiry and matches it to a related dataset to generate an output response displayed on the chatbot interface.

* User inputs inquiry/question into chatbot
* Natural language processing model determines intent of inquiry
* Inquiry is matched to related dataset using a classifier
* Output response is generated based on related dataset
* Response is displayed on chatbot interface

== Potential Applications ==
The technology can be applied in customer service chatbots, risk management systems, and educational platforms for providing information on risk-related topics.

== Problems Solved ==
This technology streamlines the process of obtaining information on risk-related topics by providing quick and accurate responses to user inquiries through a chatbot interface.

== Benefits ==
Users can easily access information on risk-related topics in real-time, improving decision-making processes and increasing efficiency in obtaining relevant information.

== Potential Commercial Applications ==
Potential commercial applications include integrating this technology into insurance companies' customer service platforms, financial institutions' risk management systems, and educational institutions' online learning platforms.

== Possible Prior Art ==
One possible prior art could be the use of chatbots in customer service applications to provide information and assistance to users. Additionally, natural language processing models have been used in various applications to analyze and interpret user inquiries.

=== Unanswered Questions ===

=== How does the system ensure the accuracy of the output responses provided to users? ===
The system may employ a feedback mechanism where users can rate the helpfulness and accuracy of the responses received. This data can be used to improve the system's matching algorithms and dataset relevance over time.

=== What measures are in place to protect user data and ensure privacy when interacting with the chatbot? ===
The system may implement encryption protocols to secure user data transmitted through the chatbot interface. Additionally, user data may be anonymized and stored securely to prevent unauthorized access or data breaches.


==Original Abstract Submitted==

A system and method employs a chatbot into which a user can input an inquiry/question regarding a risk related topic is disclosed. The user can obtain an answer to the inquiry. The system and method can receive, via a chatbot interface, an inquiry. An intent of the inquiry can be determined using a natural language processing (NLP) model. The inquiry can be matched, using a classifier, to a related data set based on the determined intent. An output can be generated based on the related data set in response to the inquiry. The output can be transmitted for display on the chatbot interface.



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