IP Library Granted Patent US 11,709,876
Granted Patent B2
US 11,709,876 · App. 17/726,126 · Granted Jul 25, 2023

Providing relevance-ordered categories of information

Inventors: Yael Shacham (Palo Alto, CA); Leland Rechis (Brooklyn, NY); Scott Jenson (Palo Alto, CA); Gabriel Wolosin (San Mateo, CA)
Assignee: GOOGLE LLC
G06F16/338G06F16/35G06F16/951
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Quick Facts
Patent No.
US 11,709,876
App. No.
17/726,126
Granted
Jul 25, 2023
Kind
B2
Abstract

A computer-implemented method is disclosed. The method includes receiving from a remote device a search query, generating a plurality of different category-directed result sets for the search query, determining an order for the plurality of category-directed result sets based on the search query, and transmitting the plurality of category-directed result sets to the remote device, in a manner that the result sets are to be displayed in the remote device in the determined order.

Claims (55)

1. A computer-implemented method, comprising:

receiving from a remote device a search query;

generating a plurality of different category-directed result sets for the search query;

calculating for each category-directed result set a likelihood value that represents a likelihood that the corresponding category-directed result set is responsive to the received search query;

comparing the calculated likelihood value to a threshold certainty value such that a likelihood value above the threshold certainty value indicates a high certainty result set;

determining an order for the plurality of category-directed result sets based on the search query; and

transmitting, from the computer server system to the remote device, code for generating a display in a manner so that a summary associated with the high certainty result set is displayed and the plurality of category-directed result sets are displayed on the remote device in the determined order.

2. The computer-implemented method of claim 1 , wherein calculating the likelihood value comprises:

retrieving a profile that is associated with the remote device and that includes a distribution of previously determined correlations between other search queries received from the remote device and one or more different categories of information; and

factoring a portion of the distribution into the calculated likelihood.

3. The computer-implemented method of claim 1 , wherein calculating the likelihood value comprises retrieving data that is associated with other search queries received from other remote devices, the other search queries being substantially similar to the received search query.

4. The computer-implemented method of claim 3 , wherein:

the data that is associated with other search queries includes a distribution of previously determined correlations between the other substantially similar search queries and one or more different categories of information; and

calculating the likelihood value further comprises factoring a portion of the distribution into the calculated likelihood.

5. The computer-implemented method of claim 4 , wherein the distribution includes multiple sub-distributions, each sub-distribution being related to any one or more of a classification of device from which the query was received, a model or model group of device from which the query was received, a geographic area from which the query was received, and an approximate time of day at which the query was received.

6. The computer-implemented method of claim 1 , wherein calculating the likelihood value comprises:

retrieving a profile that is associated with the remote device and performing a first calculation to obtain a first result based on a portion of the retrieved profile;

retrieving data that is associated with the search query and performing a second calculation to obtain a second result based on a portion of the retrieved data; and

performing a third calculation based on a weighted contribution of the first result and the second result.

7. The computer implemented method of claim 1 , further comprising determining an order of display of search results in each of the category-related result sets.

8. The computer implemented method of claim 1 , wherein the different categories correspond to categories of information selected from a group of location-based results, web results, images, video, shopping, blogs, news, maps, and books.

9. The computer implemented method of claim 1 , wherein the order of the plurality of category-related result sets is determined based on a correlation between the search query and aggregated prior user activity relating to the search query or related search queries, and categories for the result sets.

10. The computer-implemented method of claim 1 , wherein the remote device is a mobile device.

11. A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause performance of operations comprising:

generating a plurality of different category-directed result sets for the search query;

calculating for each category-directed result set a likelihood value that represents a likelihood that the corresponding category-directed result set is responsive to the received search query;

comparing the calculated likelihood value to a threshold certainty value such that a likelihood value above the threshold certainty value indicates a high certainty result set;

determining an order for the plurality of category-directed result sets based on the search query; and

transmitting, from the computer server system to the remote device, code for generating a display in a manner so that a summary associated with the high certainty result set is displayed and the plurality of category-directed result sets are displayed on the remote device in the determined order.

12. The computer-implemented method of claim 11 , wherein calculating the likelihood value comprises:

retrieving a profile that is associated with the remote device and that includes a distribution of previously determined correlations between other search queries received from the remote device and one or more different categories of information; and

factoring a portion of the distribution into the calculated likelihood.

13. The computer-implemented method of claim 11 , wherein calculating the likelihood value comprises retrieving data that is associated with other search queries received from other remote devices, the other search queries being substantially similar to the received search query.

14. The computer-implemented method of claim 13 , wherein:

the data that is associated with other search queries includes a distribution of previously determined correlations between the other substantially similar search queries and one or more different categories of information; and

calculating the likelihood value further comprises factoring a portion of the distribution into the calculated likelihood.

15. The computer-implemented method of claim 14 , wherein the distribution includes multiple sub-distributions, each sub-distribution being related to any one or more of a classification of device from which the query was received, a model or model group of device from which the query was received, a geographic area from which the query was received, and an approximate time of day at which the query was received.

16. The computer-implemented method of claim 11 , wherein calculating the likelihood value comprises:

retrieving a profile that is associated with the remote device and performing a first calculation to obtain a first result based on a portion of the retrieved profile;

retrieving data that is associated with the search query and performing a second calculation to obtain a second result based on a portion of the retrieved data; and

performing a third calculation based on a weighted contribution of the first result and the second result.

17. The computer implemented method of claim 11 , further comprising determining an order of display of search results in each of the category-related result sets.

18. A computing device, comprising:

a processor; and

a computer-readable medium having instructions stored thereon that, when executed by the processor, cause the processor to perform operations comprising:

generating a plurality of different category-directed result sets for the search query;

generating a plurality of different category-directed result sets for the search query;

calculating for each category-directed result set a likelihood value that represents a likelihood that the corresponding category-directed result set is responsive to the received search query;

comparing the calculated likelihood value to a threshold certainty value such that a likelihood value above the threshold certainty value indicates a high certainty result set;

determining an order for the plurality of category-directed result sets based on the search query; and

transmitting, from the computer server system to the remote device, code for generating a display in a manner so that a summary associated with the high certainty result set is displayed and the plurality of category-directed result sets are displayed on the remote device in the determined order.

19. The computer-implemented method of claim 18 , wherein calculating the likelihood value comprises:

retrieving a profile that is associated with the remote device and that includes a distribution of previously determined correlations between other search queries received from the remote device and one or more different categories of information; and

factoring a portion of the distribution into the calculated likelihood.

20. The computer-implemented method of claim 18 , wherein calculating the likelihood value comprises retrieving data that is associated with other search queries received from other remote devices, the other search queries being substantially similar to the received search query.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 22, 2022
From: SHACHAM, YAEL; RECHIS, LELAND; JENSON, SCOTT; WOLOSIN, GABRIEL
To: GOOGLE INC.
Reel/Frame 060276/0573 →
CHANGE OF NAME Recorded Jun 22, 2022
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 060409/0197 →
Continuity (4)
Continuation 17005713 · Aug 28, 2020
Continuation 13164550 · Jun 20, 2011
Continuation 11624175 · Jan 17, 2007
Related Publication 20220327150A1 · Oct 13, 2022