Automatically tagging topics in posts during composition thereof
US10740690B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 24, 2017 |
| Grant date | Aug 11, 2020 |
| Priority date | — |
| Expiry date | Mar 12, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N20/00
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
An online system predicts topics for content items. The online system provides one or more topic labels for a user to apply concurrently while a user is composing a post, in response to requests periodically received from the user's device. A request includes information such as content composed by the user and contextual information. The online system employs machine learning techniques to analyze content composed by a user and contextual information thereby to predict topic labels. Different machine learning models for classifying individual topic labels, identifying relevant topic labels, and/or detecting changes in existing topic predictions are developed. Some machine learning models predict topics for full content and some predict topics for partial content. The online system trains the machine learning models to ensure accurate topic predictions are provided timely. The online system employs various machine learning model training methods such as active training and gradient training.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.