Abstract

Systems and methods for implementing an artificially intelligent virtual assistant includes collecting a user query; using a competency classification machine learning model to generate a competency label for the user query; using a slot identification machine learning model to segment the text of the query and label each of the slots of the query; generating a slot value for each of the slots of the query; generating a handler for each of the slot values; and using the slot values to: identify an external data source relevant to the user query, fetch user data from the external data source, and apply one or more operations to the query to generate response data; and using the response data, to generate a response to the user query.

US20190130244A1

Links

• https://www.jasonmars.org/wp-content/uploads/2020/04/US20190130244A1.pdf

BibTeX (Download)

@misc{mars2020system,
title = {System and method for implementing an artificially intelligent virtual assistant using machine learning},
author = {Jason Mars and Lingjia Tang and Michael Laurenzano and Johann Hauswald and Parker Hill},
url = {https://www.jasonmars.org/wp-content/uploads/2020/04/US20190130244A1.pdf},
year  = {2020},
date = {2020-02-01},
abstract = {Systems and methods for implementing an artificially intelligent virtual assistant includes collecting a user query; using a competency classification machine learning model to generate a competency label for the user query; using a slot identification machine learning model to segment the text of the query and label each of the slots of the query; generating a slot value for each of the slots of the query; generating a handler for each of the slot values; and using the slot values to: identify an external data source relevant to the user query, fetch user data from the external data source, and apply one or more operations to the query to generate response data; and using the response data, to generate a response to the user query.},
note = {US Patent 10,572,801},
keywords = {Patent},
pubstate = {published},
tppubtype = {misc}
}