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. 25, 2022

Filed:

Mar. 28, 2019
Applicant:

Microsoft Technology Licensing, Llc, Redmond, WA (US);

Inventors:

Weiwei Guo, Foster City, CA (US);

Lin Guo, Saratoga, CA (US);

Jianling Zhong, San Jose, CA (US);

Huiji Gao, San Jose, CA (US);

Bo Long, Palo Alto, CA (US);

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 16/9032 (2019.01); G06N 5/04 (2006.01); G06F 16/904 (2019.01); G06F 17/16 (2006.01); G06N 3/08 (2006.01);
U.S. Cl.
CPC ...
G06F 16/90332 (2019.01); G06F 16/904 (2019.01); G06F 17/16 (2013.01); G06N 3/08 (2013.01); G06N 5/04 (2013.01);
Abstract

A neural related query generation approach in a search system uses a neural encoder that reads through a source query to build a query intent vector. The approach then processes the query intent vector through a neural decoder to emit a related query. By doing so, the approach gathers information from the entire source query before generating the related query. As a result, the neural encoder-decoder approach captures long-range dependencies in the source query such as, for example, structural ordering of query keywords. The approach can be used to generate related queries for long-tail source queries, including long-tail source queries never before or not recently submitted to the search system.


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