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US Patent 11941082 Technologies for classifying feedback using machine learning models

Patent 11941082 was granted and assigned to UL (safety organization) on March, 2024 by the United States Patent and Trademark Office.

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Contents

Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent
1

Patent attributes

Patent Applicant
UL (safety organization)
UL (safety organization)
1
Current Assignee
UL (safety organization)
UL (safety organization)
1
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
1
Patent Number
119410821
Patent Inventor Names
Christian Dorn Anschuetz1
Kyle Michael Caulfield1
Spencer Sharpe1
Surekha Durvasula1
Date of Patent
March 26, 2024
1
Patent Application Number
163832021
Date Filed
April 12, 2019
1
Patent Citations
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US Patent 10019716 Method for feedback submission resolution
1
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US Patent 10067760 System and method for classifying and resolving software production incidents
1
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US Patent 10235453 Auto-classification system and method with dynamic user feedback
1
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US Patent 10438212 Ensemble machine learning based predicting customer tickets escalation
1
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US Patent 10459951 Method and system for determining automation sequences for resolution of an incident ticket
1
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US Patent 10467630 Organizing and classifying social media conversations to improve customer service
1
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US Patent 10726060 Classification accuracy estimation
1
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US Patent 11087880 Machine model generation systems and methods
1
...
Patent Primary Examiner
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Steven B Theriault
1
CPC Code
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G06N 5/025
1
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G06N 5/02
1
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G06F 3/0482
1
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G06N 20/00
1
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G06N 5/04
1
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G06F 16/35
1
Patent abstract

Systems and methods for classifying product feedback by an electronic device are described. According to certain aspects, an electronic device may receive consumer feedback entries associated with various products, where each entry may include an initial classification. The electronic device may analyze each entry using a machine learning model to determine a subsequent classification for the entry. When there is a mismatch between classifications, the electronic device may present information associated with the entry for review by a user, where the user may specify a final classification for the entry, and the electronic device may update the machine learning model for use in subsequent analyses.

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