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:
Dec. 26, 2023

Filed:

Oct. 29, 2021
Applicant:

Home Depot Product Authority, Llc, Atlanta, GA (US);

Inventors:

Jianghong Zhou, Atlanta, GA (US);

Sayyed Zahiri, Atlanta, GA (US);

Simon Hughes, Atlanta, GA (US);

Surya Kallumadi, Atlanta, GA (US);

Khalifeh Al Jadda, Atlanta, GA (US);

Eugene Agichtein, Atlanta, GA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/2457 (2019.01); G06F 16/248 (2019.01); G06F 16/93 (2019.01); G06N 20/00 (2019.01);
U.S. Cl.
CPC ...
G06F 16/24578 (2019.01); G06F 16/248 (2019.01); G06F 16/93 (2019.01); G06N 20/00 (2019.01);
Abstract

A method for ranking documents in search results includes defining a first training data set, the first training data set including, for each of a plurality of user queries, information respective of a document selected by a user from results responsive to the query and information respective of one or more documents within an observation window after the selected document in the results, and defining a second training data set, the second training data set including, for each of the plurality of user queries, information respective of the selected document. The method further includes training a first machine learning model with the first training data set, training a second machine learning model with the second training data set, and ranking documents of a further search result set according to the output of the first machine learning model and the output of the second machine learning model.


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