Pitman-Yor process topic modeling pre-seeded by keyword groupings
US11429901B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 16, 2021 |
| Grant date | Aug 30, 2022 |
| Priority date | — |
| Expiry date | Dec 16, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N7/01
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
In one embodiment, the disclosed technology involves: digitally generating and storing a machine learning statistical topic model in computer memory, the topic model being programmed to model call transcript data representing words spoken on a call as a function of one or more topics of a set of topics that includes pre-seeded topics and non-pre-seeded topics; programmatically pre-seeding the topic model with a set of keyword groups; programmatically training the topic model using unlabeled training data; conjoining a classifier to the topic model to create a classifier model; programmatically training the classifier model using labeled training data; receiving target call transcript data; programmatically determining at least one of one or more topics of the target call or one or more classifications of the target call; and digitally storing the target call transcript data with additional data indicating the determined topics and/or classifications of the target call.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.