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:
Jan. 12, 2021

Filed:

Aug. 27, 2019
Applicant:

American Chemical Society, Washington, DC (US);

Inventors:

Mark Ryan Grabau, Westerville, OH (US);

John David Fleig, Hilliard, OH (US);

Dmitrii Arkadyevich Polshakov, Columbus, OH (US);

Jeffrey Michael Wilson, Upper Arlington, OH (US);

Rodney Laroy Fulford, Reynoldsburg, OH (US);

Yi Deng, Powell, OH (US);

Philippe Yves Ayala, Columbus, OH (US);

Donald Eugene Swartwout, Powell, OH (US);

Christopher Ryan Gessner, Columbus, OH (US);

Assignee:

American Chemical Society, Washington, DC (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/00 (2019.01); G06F 16/31 (2019.01); G06F 17/16 (2006.01); G06F 16/335 (2019.01); G06N 3/02 (2006.01); G06F 16/93 (2019.01);
U.S. Cl.
CPC ...
G06F 16/328 (2019.01); G06F 16/335 (2019.01); G06F 16/93 (2019.01); G06F 17/16 (2013.01); G06N 3/02 (2013.01);
Abstract

In some embodiments, a computer-implemented method for retrieving a similar document from a corpus of documents is provided. The method may include receiving a search document comprising a set of words; applying a first encoder to generate a first vector; applying a second encoder to generate a second vector; determining a first similarity between the first vector of the search document and the first vector of each document of the corpus of documents; determining a second similarity between the second vector of the search document and the second vector of each document of the corpus of documents; generating a first ranked list of documents based on the first similarity; generating a second ranked list of documents based on the second similarity; applying a voting algorithm to determine a score associated with each document; and outputting a third ranked list of documents based on the determined score.


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