Capturing rich response relationships with small-data neural networks
US10380260B2 · kind B2 · utility
Assignee
Inventor
Key dates
| Filing date | Dec 14, 2017 |
| Grant date | Aug 13, 2019 |
| Priority date | — |
| Expiry date | Dec 14, 2037 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/09
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.