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. 13, 2022

Filed:

Jun. 26, 2020
Applicant:

Cerner Innovation, Inc., Kansas City, KS (US);

Inventors:

David P. McCallie, Jr., Stilwell, KS (US);

Margaret Cushing Kolm, Kansas City, MO (US);

Christopher S. Finn, Liberty, MO (US);

Assignee:

Cerner Innovation, Inc., Kansas City, MO (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 16/2452 (2019.01); G06F 40/279 (2020.01); G06F 16/248 (2019.01); G06N 3/08 (2006.01); G16H 70/20 (2018.01);
U.S. Cl.
CPC ...
G06F 16/24522 (2019.01); G06F 16/248 (2019.01); G06F 40/279 (2020.01); G06N 3/08 (2013.01); G16H 70/20 (2018.01);
Abstract

In some examples, a word embedding is received. A word embedding includes a plurality of vectors in vector space. Each vector of the plurality of vectors represents a natural language word or other character sequence. Each vector is oriented in vector space based on a semantic similarity between each of the natural language word or other character sequence. A first distance is determined between a first vector and a second vector. A second distance is determined between a third vector and the second vector. Based at least in part on the first distance between the first vector and the second vector and the second distance between the third vector and the second vector, the third vector is moved closer or further away from the second vector. The moving is indicative of introducing a bias or removing a bias between the third vector and the second vector. This introducing or removing of bias supports more accurate and inclusive results from an application such as search of healthcare data, among other things.


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