Generating training datasets for a supervised learning topic model from outputs of a discovery topic model
US11410644B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 18, 2020 |
| Grant date | Aug 9, 2022 |
| Priority date | — |
| Expiry date | Sep 3, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N5/027
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Systems and methods for generating training data for a supervised topic modeling system from outputs of a topic discovery model are described herein. In an embodiment, a system receives a plurality of digitally stored call transcripts and, using a topic model, generates an output which identifies a plurality of topics represented in the plurality of digitally stored call transcripts. Using the output of the topic model, the system generates an input dataset for a supervised learning model by identify a first subset of the plurality of digitally stored call transcripts that include the particular topic, storing a positive value for the first subset, identifying a second subset that do not include the particular topic, and storing a negative value for the second subset. The input training dataset is then used to train a supervised learning model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.