- Patent Title: Automatically tagging topics in posts during composition thereof
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Application No.: US15469399Application Date: 2017-03-24
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Publication No.: US10740690B2Publication Date: 2020-08-11
- Inventor: Jeffrey William Pasternack , David Vickrey , Justin MacLean Coughlin , Prasoon Mishra , Austen Norment McDonald , Max Christian Eulenstein , Jianfu Chen , Kritarth Anand , Polina Kuznetsova
- Applicant: Facebook, Inc.
- Applicant Address: US CA Menlo Park
- Assignee: Facebook, Inc.
- Current Assignee: Facebook, Inc.
- Current Assignee Address: US CA Menlo Park
- Agency: Fenwick & West LLP
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06F16/35 ; G06N5/04 ; G06N20/20

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.
Public/Granted literature
- US20180276561A1 AUTOMATICALLY TAGGING TOPICS IN POSTS DURING COMPOSITION THEREOF Public/Granted day:2018-09-27
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