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US Patent 11373044 Maintaining machine language model state across communications channels

Patent 11373044 was granted and assigned to ASAPP on June, 2022 by the United States Patent and Trademark Office.

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Contents

Is a
Patent
Patent

Patent attributes

Patent Applicant
ASAPP
ASAPP
Current Assignee
ASAPP
ASAPP
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
11373044
Patent Inventor Names
Tao Lei0
Joseph Ellsworth Hackman0
Christopher David Fox0
Date of Patent
June 28, 2022
Patent Application Number
16503528
Date Filed
July 4, 2019
Patent Citations
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US Patent 10044647 Systems and methods for controlling enrollment and secure persistent SMS texting account servicing with an intelligent assistant
0
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US Patent 10083451 Using semantic processing for customer support
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US Patent 10088972 Virtual assistant conversations
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US Patent 10097690 Detecting events from customer support sessions
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US Patent 10109275 Word hash language model
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US Patent 10169315 Removing personal information from text using a neural network
0
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US Patent 10210244 Updating natural language interfaces by processing usage data
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US Patent 10395648 Analysis of a topic in a communication relative to a characteristic of the communication
0
...
Patent Citations Received
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US Patent 11956187 Natural language processing for information extraction
0
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US Patent 11588760 Initialization of automated workflows
0
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US Patent 11588759 Automated communications over multiple channels
0
Patent Primary Examiner
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Satwant K Singh

Machine learning models may be used during a communications session to process natural language communications and perform actions relating to the communications session. For example, a machine learning model may be used to provide an automated response to a user, to suggest a completion of text being entered by a user, or to provide information about a relevant resource. Machine learning models may rely on machine learning model data that is updated during a communications session as communications are processed by the machine learning model. To improve the performance of a machine learning model when a user leaves a first communications session and enters a second communications session, the machine learning model data may be stored during a first communications session and then retrieved during the second communications session to initialize a machine learning model for the second communications session.

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