Machine learning for associating skills with content

US11531928B2 · kind B2 · utility

Assignee

• MICROSOFT TECHNOLOGY LICENSING, LLC · US

Inventors

• Shivani Rao · Mumbai, IN
• Deepak Kumar · Sunnyvale, US
• Zhe Cui · Greenbelt, US
• Bonnie Bills · Livermore, US
• Seyedmohsen Jamali · Sunnyvale, US
• Siyuan Zhang · Mountain View, US
• Gungor Polatkan · San Jose, US

Key dates

• Filing date: Jun 30, 2018
• Grant date: Dec 20, 2022
• Expiry date: Apr 3, 2041

Classification

• Technology area (CPC G): Physics
• CPC primary: G06N20/10
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

Techniques are provided for using machine learning techniques to associate skills with different content. In one technique, multiple classifications models are trained. Each classification model corresponds to a different skill and is trained based on textual embeddings of a plurality of content items and labels indicating whether each content item is associated with the skill that corresponds to that classification model. A particular content item embedding is generated based on text from a particular content item. The particular content item embedding is applied to the classification models to generate multiple results. One or more results of the multiple results are identified that indicate that one or more corresponding skills are associated with the particular content item. For each result of the one or more results, skill tagging data are stored that associate the particular content item with a particular skill that corresponds to that result.