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.

Date of Patent:
Oct. 25, 2022

Filed:

Oct. 29, 2018
Applicant:

Google Llc, Mountain View, CA (US);

Inventors:

Thomas Mieczyslaw Kwiatkowski, Brooklyn, NY (US);

Ankur P. Parikh, New York, NY (US);

Swabha Swayamdipta, Seattle, WA (US);

Assignee:

Google LLC, Mountain View, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 15/00 (2006.01); G06N 3/08 (2006.01); G06N 5/04 (2006.01); G06F 40/30 (2020.01); G06K 9/62 (2022.01); G06N 3/04 (2006.01); G06V 30/40 (2022.01);
U.S. Cl.
CPC ...
G06N 5/04 (2013.01); G06F 40/30 (2020.01); G06K 9/6215 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06V 30/40 (2022.01);
Abstract

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for selecting a text span from an input electronic document that answers an input question. One of the methods includes obtaining a respective first numeric representations of text spans in the input document; for each of the text spans: determining, for a segment that contains the text span, a question-aware segment vector, determining, for the question, a segment-aware question vector, and processing the first numeric representation of the text span, the question-aware segment vector, and the segment-aware question vector using a second feedforward neural network to generate a second numeric representation of the text span; for each unique text span in the plurality of text spans: determining an aggregate representation for the unique text span, and determining, from the aggregate representation, a final score for the unique text span; and selecting a unique text span.


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