Invention Grant
- Patent Title: Capturing rich response relationships with small-data neural networks
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Application No.: US16915758Application Date: 2020-06-29
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Publication No.: US11657231B2Publication Date: 2023-05-23
- Inventor: John Hewitt
- Applicant: QUALTRICS, LLC
- Applicant Address: US UT Provo
- Assignee: Qualtrics, LLC
- Current Assignee: Qualtrics, LLC
- Current Assignee Address: US UT Provo
- Agency: Keller Preece PLLC
- Main IPC: G06F40/30
- IPC: G06F40/30 ; G06N3/08 ; G06N3/04 ; G06F40/205 ; G06F40/216 ; G06F40/253 ; G06F40/268 ; G06F40/284

Abstract:
The present disclosure relates to a response analysis system that employs a small-data training dataset to train a neural network that accurately performs domain-agnostic opinion mining. For example, in one or more embodiments, the response analysis system trains a response classification neural network using part of speech information (e.g., syntactic information) to learn and apply response classification labels for opinion text responses. In particular, the response analysis system employs part of speech information patterns without regard to word patterns to determine whether words in a text response correspond to an opinion, the target of the opinion, or neither. In addition, the trained response classification neural network has a significantly reduced learned parameter space, which decreases processing, memory requirements, and overall complexity.
Public/Granted literature
- US20200342177A1 CAPTURING RICH RESPONSE RELATIONSHIPS WITH SMALL-DATA NEURAL NETWORKS Public/Granted day:2020-10-29
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