US 12,079,714 B2
Methods and systems for an artificial intelligence advisory system for textual analysis
Kenneth Neumann, Lakewood, CO (US)
Assigned to KPN INNOVATIONS, LLC, Lakewood, CO (US)
Filed by Kenneth Neumann, Lakewood, CO (US)
Filed on Jul. 3, 2019, as Appl. No. 16/502,797.
Prior Publication US 2021/0005316 A1, Jan. 7, 2021
Int. Cl. G06F 16/30 (2019.01); G06F 16/9032 (2019.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G06F 40/205 (2020.01)
CPC G06N 3/08 (2013.01) [G06F 16/90332 (2019.01); G06N 20/00 (2019.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G06F 40/205 (2020.01)] 20 Claims
OG exemplary drawing
 
1. An artificial intelligence advisory system for textual analysis, the system comprising:
at least a server, wherein the at least a server is configured to:
receive at least a user input datum from a user client device of a user;
an advisory module operating on the at least a server, wherein the advisory module is configured to:
receive at least an advisory input from an advisor client device, wherein the advisory input comprises an advisory recommendation for the user to engage in a specific spiritual practice; and
generate at least an advisory instruction set as a function of the at least a user input datum and the at least an advisory input;
a label learner operating on the at least a server, wherein the label learner generates a plurality of advisory labels tailored to the user, wherein generating the plurality of advisory labels comprises:
determine a correctness probability for each of the plurality of advisory labels;
filter the plurality of advisory labels as a function of comparing the correctness probability for each of the plurality of advisory labels and a correctness probability threshold; and
an artificial intelligence advisor operating on the at least a server, wherein the artificial intelligence advisor is configured to:
generate at least a textual output as a function of the at least an advisory instruction set and the at least a user input datum;
receive at least a user input as a function of the at least a textual output through the user client device via an instant messaging protocol of the at least a server, wherein the at least a user input includes text;
verify the at least a user input as a function of a geolocation of the user;
communicate the at least a user input to the advisory module through a parsing module, wherein the parsing module is configured to classify a polarity of the text of the at least a user input and generate at least a query as a function of the at least a user input;
determine an informational response for the user as a function of the at least a query;
detect a consultation event using a consultation model configured to classify the user input to the consultation event, wherein the consultation model is trained with a training data set correlating keywords, from a keyword listing populated with expert data inputs, and phrases from a corpus that a supervised learning module has associated with consultation events; and
provide the informational response and the consultation event to the user client device through the instant messaging protocol of the at least a server.