US Patent:
20180276561, Sep 27, 2018
Inventors:
- Menlo Park CA, US
David Vickrey - Mountain View CA, US
Justin MacLean Coughlin - Redwood City CA, US
Prasoon Mishra - Mountain View CA, US
Austen Norment McDonald - Sunnyvale CA, US
Max Christian Eulenstein - San Francisco CA, US
Jianfu Chen - Mountain View CA, US
Kritarth Anand - Redwood City CA, US
Polina Kuznetsova - Mountain View CA, US
International Classification:
G06N 99/00
G06N 7/00
G06F 17/30
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.
