US 2020/0004886 A1Published application

Generating supervised embedding representations for search

AssigneeMicrosoft Technology Licensing, LLC

InventorsRohan Ramanath, Gungor Polatkan, Qi Guo, Cagri Ozcaglar, Krishnaram Kenthapadi, Sahin Cem Geyik

Life of this patent

Estimating the term…

Loading patent…

Abstract

Techniques for generating supervised embedding representations for search are disclosed herein. In some embodiments, a computer system receives training data comprising query representations including an entity included in a corresponding search query submitted by a querying user, search result representations for each one of the query representations, and user actions for each one of the query representations, and generates a corresponding embedding vector for each one of the at least one entity using a supervised learning algorithm and the received training data. In some example embodiments, the corresponding search result representations for each one of the query representations represents a plurality of candidate users displayed in response to the search queries based on profile data of the candidate users, and the user actions comprise actions by the querying user directed towards at least one candidate user in the search results.

Claims20

Dependent claims

A computer-implemented method comprising:

receiving, by a computer system having a memory and at least one hardware processor, training data comprising a plurality of query representations, a plurality of search result representations for each one of the plurality of query representations, and a plurality of user actions for each one of the plurality of query representations, each one of the plurality of query representations representing at least one entity included in a corresponding search query submitted by a querying user, the corresponding plurality of search result representations for each one of the plurality of query representations representing a plurality of candidate users displayed in response to the plurality of search queries based on profile data of the plurality of candidate users stored on a database of an online service, the plurality of user actions comprising actions by the querying user directed towards at least one candidate user of the plurality of search results for the corresponding search query;
generating, by the computer system, a corresponding embedding vector for each one of the at least one entity using a supervised learning algorithm and the received training data;
and
performing, by the computer system, a function of the online service using the generated embedding vector for each one of the at least one entity.

1 more element

A system comprising:

at least one hardware processor;
and
a non-transitory machine-readable medium embodying a set of instructions that, when executed by at least one hardware processor, cause the processor to perform operations, the operations comprising:
receiving training data comprising a plurality of query representations, a plurality of search result representations for each one of the plurality of query representations, and a plurality of user actions for each one of the plurality of query representations, each one of the plurality of query representations representing at least one entity included in a corresponding search query submitted by a querying user, the corresponding plurality of search result representations for each one of the plurality of query representations representing a plurality of candidate users displayed in response to the plurality of search queries based on profile data of the plurality of candidate users stored on a database of an online service, the plurality of user actions comprising actions by the querying user directed towards at least one candidate user of the plurality of search results for the corresponding search query;
generating a corresponding embedding vector for each one of the at least one entity using a supervised learning algorithm and the received training data;
and
performing a function of the online service using the generated embedding vector for each one of the at least one entity.

4 more elements

A non-transitory machine-readable medium embodying a set of instructions that, when executed by at least one hardware processor, cause the processor to perform operations comprising:

receiving training data comprising a plurality of query representations, a plurality of search result representations for each one of the plurality of query representations, and a plurality of user actions for each one of the plurality of query representations, each one of the plurality of query representations representing at least one entity included in a corresponding search query submitted by a querying user, the corresponding plurality of search result representations for each one of the plurality of query representations representing a plurality of candidate users displayed in response to the plurality of search queries based on profile data of the plurality of candidate users stored on a database of an online service, the plurality of user actions comprising actions by the querying user directed towards at least one candidate user of the plurality of search results for the corresponding search query;
generating a corresponding embedding vector for each one of the at least one entity using a supervised learning algorithm and the received training data;
and
performing a function of the online service using the generated embedding vector for each one of the at least one entity.

1 more element

Dependencies are inferred from the claim text.