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:
May. 12, 2020
Filed:
May. 14, 2018
Microsoft Technology Licensing, Llc, Redmond, WA (US);
Bill Dolan, Redmond, WA (US);
Margaret Mitchell, Redmond, WA (US);
Jay Banerjee, Redmond, WA (US);
Pallavi Choudhury, Redmond, WA (US);
Susan Hendrich, Redmond, WA (US);
Rebecca Mason, Redmond, WA (US);
Ron Owens, Redmond, WA (US);
Mouni Reddy, Redmond, WA (US);
Yaxiao Song, Redmond, WA (US);
Kristina Toutanova, Redmond, WA (US);
Liang Xu, Redmond, WA (US);
Xuetao Yin, Redmond, WA (US);
MICROSOFT TECHNOLOGY LICENSING, LLC, Redmond, WA (US);
Abstract
A 'Facet Recommender' creates conversational recommendations for facets of particular conversational topics, and optionally for things associated with those facets, from consumer reviews or other social media content. The Facet Recommender applies a machine-learned facet model and optional sentiment-model, to identify facets associated with spans or segments of the content and to determine neutral, positive, or negative consumer sentiment associated with those facets and, optionally, things associated with those facets. These facets are selected by the facet model from a list or set of manually defined or machine-learned facets for particular conversational topic types. The Facet Recommender then generates new conversational utterances (i.e., short neutral, positive or negative suggestions) about particular facets based on the sentiments associated with those facets. In various implementations, utterances are fit to one or more predefined conversational frameworks. Further, responses or suggestions provided as utterances may be personalized to individual users.