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:
Aug. 24, 2021

Filed:

Apr. 30, 2019
Applicant:

A9.com, Inc., Palo Alto, CA (US);

Inventors:

Cuize Han, San Jose, CA (US);

Nikhil Rao, San Jose, CA (US);

Daria Sorokina, San Carlos, CA (US);

Karthik Subbian, Fremont, CA (US);

Assignee:

A9.COM, INC., Palo Alto, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/535 (2019.01); G06N 20/20 (2019.01); G06F 16/583 (2019.01); G06F 16/587 (2019.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
G06F 16/535 (2019.01); G06F 16/587 (2019.01); G06F 16/5846 (2019.01); G06N 3/08 (2013.01); G06N 20/20 (2019.01);
Abstract

Various embodiments provide for selecting a subset of features to use to train a model for search applications. To select a feature, the candidate features are randomly assigned into two groups. Each of the two groups represents a summation of the respective features that were assigned to it. Then a decision tree building scan is performed on the two groups to determine which of the two groups performs better based a selection criteria. Upon determining which of the two groups is better, the candidate features of the winning group are again randomly assigned into two groups. These two groups are again scanned as described above to determine a winning group. This binary splitting and scanning pattern is continuously performed until the winning group contains one remaining feature. That remaining feature is then designated as a selected feature to be used in the search model.


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