US 11,899,901 B2
Computer-implemented natural language processing for virtual environment interactions
Jeffrey Michael Freisthler, Ann Arbor, MI (US); Justin Wayne Webster, Omaha, NE (US); Christopher Nathan Melnick, Ellisville, MO (US); Bryan Edelman, St. Louis, MO (US); Nathan Ralph Hogge, Brighton, MI (US); and Jacob Patrick Sullivan, Belleville, IL (US)
Assigned to Charles Schwab & Co., Inc., San Francisco, CA (US)
Filed by TD Ameritrade IP Company, Inc., Omaha, NE (US)
Filed on Jul. 19, 2021, as Appl. No. 17/378,938.
Claims priority of provisional application 63/110,832, filed on Nov. 6, 2020.
Prior Publication US 2022/0147225 A1, May 12, 2022
Int. Cl. G06F 3/048 (2013.01); G06F 3/04815 (2022.01); H04L 12/18 (2006.01); H04L 51/046 (2022.01)
CPC G06F 3/04815 (2013.01) [H04L 12/1895 (2013.01); H04L 51/046 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for facilitating real-time user interactions in a virtual environment of a user application accessible by a plurality of computing devices, the system comprising:
processor hardware; and
memory hardware configured to store instructions, the processor hardware configured to execute the instructions and cause the system to perform,
receiving a set of defined topics including a defined topic from a first computing device of the plurality of computing devices;
receiving, from at least one of the plurality of computing devices, data representing machine-readable text converted from a verbal conversation between two or more users in the virtual environment of the user application;
identifying a set of topics from the data representing machine-readable text:
comparing the identified set of topics from the data representing machine-readable text to the set of defined topics;
in response to detecting a match between a topic of the identified set of topics and the defined topic of the set of defined topics, determining a relevancy value of the topic of the identified set of topics, wherein the relevancy value is a weighted average indicating a degree of importance for the topic as compared to other topics of the identified set of topics based on at least one or more data feeds providing information from one or more internet sources; and
transmitting, to the first computing device, a notification of the matching defined topic only if the relevancy value of the topic is greater than a threshold value.