View source for 18478145. APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR TRAINING A VIRTUAL AGENT ARTIFICIAL INTELLIGENCE MODEL simplified abstract (Atlassian Pty Ltd.)

=APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR TRAINING A VIRTUAL AGENT ARTIFICIAL INTELLIGENCE MODEL=


==Organization Name==

[[:Category:Atlassian Pty Ltd.|Atlassian Pty Ltd.]]


[[Category:Atlassian Pty Ltd.]]

==Inventor(s)==

[[:Category:Deyang Zhao of San Francisco CA (US)|Deyang Zhao of San Francisco CA (US)]][[Category:Deyang Zhao of San Francisco CA (US)]]

[[:Category:Zhou Sha of San Francisco CA (US)|Zhou Sha of San Francisco CA (US)]][[Category:Zhou Sha of San Francisco CA (US)]]

==APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR TRAINING A VIRTUAL AGENT ARTIFICIAL INTELLIGENCE MODEL - A simplified explanation of the abstract==


This abstract first appeared for US patent application 18478145 titled 'APPARATUSES, METHODS, AND COMPUTER PROGRAM PRODUCTS FOR TRAINING A VIRTUAL AGENT ARTIFICIAL INTELLIGENCE MODEL

==Simplified Explanation==

The patent application describes a method for training a virtual agent artificial intelligence model using an IT support label dataset and a training dataset associated with candidate questions provided by a classification model. The trained AI model is then used to configure an intent recognition engine for a virtual agent system.

* Explanation of the patent:
** IT support label dataset generated from service event data structures
** Training dataset associated with candidate questions
** Training of AI model based on the datasets
** Configuration of intent recognition engine for virtual agent system

== Potential Applications ==
The technology can be applied in various industries for developing virtual agent systems for customer support, IT service management, and automated assistance.

== Problems Solved ==
The technology helps in improving the efficiency and accuracy of virtual agent systems by training AI models with relevant datasets, leading to better understanding and response to user queries.

== Benefits ==
The benefits of this technology include enhanced customer service, reduced response times, improved problem-solving capabilities, and overall better user experience.

== Potential Commercial Applications ==
The technology can be used in customer service applications, IT helpdesk support, chatbots for e-commerce websites, and other automated assistance systems.

== Possible Prior Art ==
Prior art in this field may include existing virtual agent systems, AI models for intent recognition, and datasets used for training AI in customer service applications.

== Unanswered Questions ==
=== How does the technology handle complex or ambiguous user queries? ===
The patent application does not provide specific details on how the AI model is trained to handle complex or ambiguous user queries.

=== What is the scalability of the technology for large-scale applications? ===
The scalability of the technology for large-scale applications is not addressed in the patent application.


==Original Abstract Submitted==

Methods, apparatuses, or computer program products provide for training a virtual agent artificial intelligence model. An information technology (IT) support label dataset is generated based on service event data structures related to respective services messages provided to an application framework configured to manage respective application components for IT service management. Additionally a training dataset associated with a set of candidate questions provided by a classification model is generated and an artificial intelligence (AI) model is trained based on the IT support label dataset and the training dataset to generate a trained AI model. An intent recognition engine for a virtual agent system is then configured based on the trained AI model.



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