The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Oct. 04, 2022
Filed:
Dec. 29, 2020
Microsoft Technology Licensing, Llc, Redmond, WA (US);
Yiming Wang, Sunnyvale, CA (US);
Xiao Yan, Sunnyvale, CA (US);
Lin Zhu, Santa Clara, CA (US);
Jaewon Yang, Sunnyvale, CA (US);
Yanen Li, Foster City, CA (US);
Jacob Bollinger, San Francisco, CA (US);
Microsoft Technology Licensing, LLC, Redmond, WA (US);
Abstract
Techniques for ranking skills using an ensemble machine learning approach are described. The outputs of two heterogenous, machine-learned models are combined to rank a set of skills that may be possessed by an end-user of an online service. Some subset of the highest-ranking skills is then presented to the end-user with a recommendation that the skills be added to the end-user's profile. The ensemble learning technique involves a concept referred to as 'boosting', in which a weaker performing model is enhanced (e.g., 'boosted') by a stronger performing model, when ranking the set of skills. Accordingly, by using a combination of models, better results are achieved than might be with either one of the individual models alone. Furthermore, the approach is scalable in ways that cannot be achieved with heuristic-based approaches.