IP Library Granted Patent US 10,521,479
Granted Patent B2
US 10,521,479 · App. 16/416,842 · Granted Dec 31, 2019

Evaluating semantic interpretations of a search query

Inventors: Ashish Venugopal (Jersey City, NJ); Jakob D. Uszkoreit (Portola Valley, CA); John Blitzer (Mountain View, CA); Edward Everett Anderson (Mountain View, CA)
Assignee: Google LLC
G06F16/951G06F16/334
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Quick Facts
Patent No.
US 10,521,479
App. No.
16/416,842
Granted
Dec 31, 2019
Kind
B2
Abstract

The present disclosure relates to evaluating different semantic interpretations of a search query. One example method includes obtaining a set of search results for a particular search query submitted to a search engine; obtaining a set of semantic interpretations for the particular search query; obtaining, for each semantic interpretation of the set, a canonical search query; generating a modified search query based at least in part on the particular search query and the canonical search query for the semantic interpretation; obtaining a set of search results for the modified search query for the semantic interpretation; and determining, for each semantic interpretation of the set, a degree of similarity between (i) the set of search results of the modified search query for the semantic interpretation, and (ii) the set of search results for the particular search query.

Claims (52)

1. A computer-implemented method executed by one or more processors, the method comprising:

obtaining a set of search results for a particular search query submitted to a search engine, wherein the particular search query includes a substring that is a subset of terms of the query, and where the subset of terms can identify a plurality of different entities;

obtaining a set of semantic interpretations for the particular search query, each semantic interpretation representing a candidate intent associated with a particular entity, wherein each particular entity is different from each other particular entity and is one of the plurality of different entities;

obtaining, for each semantic interpretation of the set, a canonical search query;

generating, for each semantic interpretation of the set, a modified search query based at least in part on the particular search query and the canonical search query for the semantic interpretation, wherein generating the modified search query for each semantic interpretation includes:

modifying, in the particular search query, the substring included in the particular search query to include (i) the substring of terms and (ii) a second set of terms from the canonical search query for the semantic interpretation;

wherein the second set of terms were not included in the particular search query;

the substring of terms and the second set of terms identity the particular entity associated with the candidate intent for the canonical query;

obtaining, for each semantic interpretation of the set, a set of search results for the modified search query for the semantic interpretation;

determining, for each semantic interpretation of the set:

a degree of similarity between (i) the set of search results of the modified search query for the semantic interpretation, and (ii) the set of search results for the particular search query;

wherein determining the degree of similarity is based at least in part on comparing attributes of the set of search results for the modified search query with attributes of the set of search results for the particular search query; and

selecting a particular semantic interpretation of the set of semantic interpretations based on the degrees of similarity between the set of search results of the modified search query for the particular semantic interpretation and the set of search results for the particular search query.

2. The method of claim 1 , wherein generating the modified search query for each semantic interpretation includes reformatting the particular search query to match the canonical search query for the semantic interpretation.

3. The method of claim 1 , wherein determining the degree of similarity is based at least in part on the size of an intersection between the set of search results for the modified search query and the set of search results for the particular search query.

4. The method of claim 1 , wherein determining the degree of similarity is based at least in part on the size of a difference between the set of search results for the modified search query and the set of search results for the particular search query.

5. The method of claim 1 , wherein determining the degree of similarity is based at least in part on the frequency of occurrence of particular keywords associated with the particular search query in the set of search results for the modified search query and the set of search results for the particular search query.

6. The method of claim 1 , wherein determining the degree of similarity is based at least in part on comparing an order of the set of search results for the modified search query with an order of the set of search results for the particular search query.

7. A non-transitory, computer-readable medium storing instructions operable when executed to cause at least one processor to perform operations comprising:

obtaining a set of search results for a particular search query submitted to a search engine, wherein the particular search query includes a substring that is a subset of terms of the query, and where the subset of terms can identify a plurality of different entities;

obtaining a set of semantic interpretations for the particular search query, each semantic interpretation representing a candidate intent associated with a particular entity, wherein each particular entity is different from each other particular entity and is one of the plurality of different entities;

obtaining, for each semantic interpretation of the set, a canonical search query;

generating, for each semantic interpretation of the set, a modified search query based at least in part on the particular search query and the canonical search query for the semantic interpretation, wherein generating the modified search query for each semantic interpretation includes:

modifying, in the particular search query, the substring included in the particular search query to include (i) the substring of terms and (ii) a second set of terms from the canonical search query for the semantic interpretation;

wherein the second set of terms were not included in the particular search query;

the substring of terms and the second set of terms identity the particular entity associated with the candidate intent for the canonical query;

obtaining, for each semantic interpretation of the set, a set of search results for the modified search query for the semantic interpretation;

determining, for each semantic interpretation of the set:

a degree of similarity between (i) the set of search results of the modified search query for the semantic interpretation, and (ii) the set of search results for the particular search query;

wherein determining the degree of similarity is based at least in part on comparing attributes of the set of search results for the modified search query with attributes of the set of search results for the particular search query; and

selecting a particular semantic interpretation of the set of semantic interpretations based on the degrees of similarity between the set of search results of the modified search query for the particular semantic interpretation and the set of search results for the particular search query.

8. The computer-readable medium of claim 7 , wherein generating the modified search query for each semantic interpretation includes reformatting the particular search query to match the canonical search query for the semantic interpretation.

9. The computer-readable medium of claim 7 , wherein determining the degree of similarity is based at least in part on the size of an intersection between the set of search results for the modified search query and the set of search results for the particular search query.

10. The computer-readable medium of claim 7 , wherein determining the degree of similarity is based at least in part on the size of a difference between the set of search results for the modified search query and the set of search results for the particular search query.

11. The computer-readable medium of claim 7 , wherein determining the degree of similarity is based at least in part on the frequency of occurrence of particular keywords associated with the particular search query in the set of search results for the modified search query and the set of search results for the particular search query.

12. The computer-readable medium of claim 7 , wherein determining the degree of similarity is based at least in part on comparing an order of the set of search results for the modified search query with an order of the set of search results for the particular search query.

13. A system comprising:

memory for storing data and instructions executable by one or more processors; and

one or more processors that execute the instructions and in response perform operations comprising:

obtaining a set of search results for a particular search query submitted to a search engine, wherein the particular search query includes a substring that is a subset of terms of the query, and where the subset of terms can identify a plurality of different entities;

obtaining a set of semantic interpretations for the particular search query, each semantic interpretation representing a candidate intent associated with a particular entity, wherein each particular entity is different from each other particular entity and is one of the plurality of different entities;

obtaining, for each semantic interpretation of the set, a canonical search query;

generating, for each semantic interpretation of the set, a modified search query based at least in part on the particular search query and the canonical search query for the semantic interpretation, wherein generating the modified search query for each semantic interpretation includes:

modifying, in the particular search query, the substring included in the particular search query to include (i) the substring of terms and (ii) a second set of terms from the canonical search query for the semantic interpretation;

wherein the second set of terms were not included in the particular search query;

the substring of terms and the second set of terms identity the particular entity associated with the candidate intent for the canonical query;

obtaining, for each semantic interpretation of the set, a set of search results for the modified search query for the semantic interpretation;

determining, for each semantic interpretation of the set:

a degree of similarity between (i) the set of search results of the modified search query for the semantic interpretation, and (ii) the set of search results for the particular search query;

wherein determining the degree of similarity is based at least in part on comparing attributes of the set of search results for the modified search query with attributes of the set of search results for the particular search query; and

selecting a particular semantic interpretation of the set of semantic interpretations based on the degrees of similarity between the set of search results of the modified search query for the particular semantic interpretation and the set of search results for the particular search query.

14. The system of claim 13 , wherein generating the modified search query for each semantic interpretation includes reformatting the particular search query to match the canonical search query for the semantic interpretation.

Assignments (2)
CHANGE OF NAME Recorded Sep 18, 2019
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 050411/0900 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 21, 2019
From: VENUGOPAL, ASHISH; USZKOREIT, JAKOB D.; BLITZER, JOHN; ANDERSON, EDWARD EVERETT
To: GOOGLE INC.
Reel/Frame 049238/0019 →
Continuity (3)
Continuation 14644803 · Mar 11, 2015
Provisional Application 62050627 · Sep 15, 2014
Related Publication 20190278813A1 · Sep 12, 2019