IP Library Granted Patent US 9,940,372
Granted Patent B2
US 9,940,372 · App. 14/720,867 · Granted Apr 10, 2018

Triggering method for instant search

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Quick Facts
Patent No.
US 9,940,372
App. No.
14/720,867
Granted
Apr 10, 2018
Kind
B2
Abstract

Techniques are provided for automatically determining when to trigger instant search. In one technique, while a user is entering text to formulate a search query, and prior to receiving an indication that the user has completed formulation of the search query, a search assistant system determines the most popular queries that include the text the user has already entered. The search assistant system then determines whether to proactively provide, to the user, search results for the top-candidate of those completed queries. That determination may take into account factors such as whether the top-candidate qualifies as a dominant completed query, a richness metric determined for the search results for the particular completed query, and/or a satisfaction metric determined for the search results for the particular completed query. If the search assistant system determines to proactively provide search results for the particular completed query, the search results for the particular completed query are presented to the user prior to receiving any indication that the user has completed formulation of the search query.

Claims (73)

1. A method comprising:

while a user is entering text to formulate a search query, and prior to receiving an indication that the user has completed formulation of the search query, performing the steps of:

determining a plurality of completed queries that include the text the user has already entered for the search query;

determining whether to proactively provide, to the user, search results for a particular completed query of the plurality of completed queries;

wherein determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on at least one of:

whether the particular completed query qualifies as a dominant completed query;

a richness metric determined for the search results for the particular completed query; or

satisfaction metric determined for the search results for the particular completed query; and

responsive to determining to proactively provide search results for the particular completed query, causing presentation of the search results for the particular completed query to the user prior to receiving the indication that the user has completed formulation of the search query;

wherein the method is performed by one or more computing devices.

2. The method of claim 1 wherein determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on whether the particular completed query qualifies as a dominant completed query.

3. The method of claim 2 further comprising:

determining a probable-intent score for the particular completed query;

wherein the probable-intent score indicates likelihood that the user intends to enter the particular completed query;

performing a comparison between the probable-intent score and a dominant-intent-threshold; and

determining whether the particular completed query qualifies as a dominant completed query based on the comparison between the probable-intent score and the dominant-intent-threshold.

4. The method of claim 3 further comprising determining the dominant-intent-threshold based, at least in part, on how many characters of text the user has entered.

5. The method of claim 1 wherein determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on the richness metric determined for the search results for the particular completed query.

6. The method of claim 5 wherein the richness metric is based, at least in part, on which types of content are contained in the search results for the particular completed query.

7. The method of claim 1 wherein:

the method further comprises monitoring how users that have previously submitted the particular completed query have interacted with the search results for the particular completed query;

based on how users that have previously submitted the particular completed query have interacted with the search results for the particular completed query, determining the satisfaction metric associated with the search results for the particular completed query; and

determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on the satisfaction metric determined for the search results for the particular completed query.

8. The method of claim 1 wherein:

the method further comprises:

for each training query from a set of training queries, feeding a plurality of features relating to the training query into a machine learning tool to train the machine learning tool;

after training the machine learning tool, producing particular output by feeding particular features relating to the particular completed query to the machine learning tool; and

the step of determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on the particular output.

9. The method of claim 1 wherein:

the step of determining a plurality of completed queries comprises:

identifying a first set of completed queries, wherein the first set of completed queries are completed queries that include the text;

determining a second set of completed queries, wherein the second set of completed queries are completed queries, from the first set, that satisfy certain criteria;

determining a third set of completed queries, wherein the third set of completed queries are completed queries, from the second set, that are most popular; and

the particular completed query is a most popular query from the third set of completed queries.

10. The method of claim 9 wherein the certain criteria includes that the queries were sent by users that match one or more characteristics of the user that is formulating the search query.

11. The method of claim 9 wherein the certain criteria includes that the queries were sent at a time that matches a time at which the user that is formulating the search query.

12. The method of claim 9 wherein the certain criteria includes that the queries were sent from locations that match location information related to the user that is formulating the search query.

13. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of a method comprising:

while a user is entering text to formulate a search query, and prior to receiving an indication that the user has completed formulation of the search query, performing the steps of:

determining a plurality of completed queries that include the text the user has already entered for the search query;

determining whether to proactively provide, to the user, search results for a particular completed query of the plurality of completed queries;

wherein determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on at least one of:

whether the particular completed query qualifies as a dominant completed query;

a richness metric determined for the search results for the particular completed query; or

satisfaction metric determined for the search results for the particular completed query; and

responsive to determining to proactively provide search results for the particular completed query, causing presentation of the search results for the particular completed query to the user prior to receiving the indication that the user has completed formulation of the search query.

14. The one or more non-transitory storage media of claim 13 wherein determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on whether the particular completed query qualifies as a dominant completed query.

15. The one or more non-transitory storage media of claim 14 wherein the method further comprises:

determining a probable-intent score for the particular completed query;

wherein the probable-intent score indicates likelihood that the user intends to enter the particular completed query;

performing a comparison between the probable-intent score and a dominant-intent-threshold; and

determining whether the particular completed query qualifies as a dominant completed query based on the comparison between the probable-intent score and the dominant-intent-threshold.

16. The one or more non-transitory storage media of claim 15 wherein the method further comprises determining the dominant-intent-threshold based, at least in part, on how many characters of text the user has entered.

17. The one or more non-transitory storage media of claim 13 wherein determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on the richness metric determined for the search results for the particular completed query.

18. The one or more non-transitory storage media of claim 17 wherein the richness metric is based, at least in part, on which types of content are contained in the search results for the particular completed query.

19. The one or more non-transitory storage media of claim 13 wherein:

the method further comprises monitoring how users that have previously submitted the particular completed query have interacted with the search results for the particular completed query;

based on how users that have previously submitted the particular completed query have interacted with the search results for the particular completed query, determining the satisfaction metric associated with the search results for the particular completed query; and

determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on the satisfaction metric determined for the search results for the particular completed query.

20. The one or more non-transitory storage media of claim 13 wherein:

the method further comprises:

for each training query from a set of training queries, feeding a plurality of features relating to the training query into a machine learning tool to train the machine learning tool;

after training the machine learning tool, producing particular output by feeding particular features relating to the particular completed query to the machine learning tool; and

the step of determining whether to proactively provide, to the user, search results for the particular completed query is based, at least in part, on the particular output.

21. The one or more non-transitory storage media of claim 13 wherein:

the step of determining a plurality of completed queries comprises:

identifying a first set of completed queries, wherein the first set of completed queries are completed queries that include the text;

determining a second set of completed queries, wherein the second set of completed queries are completed queries, from the first set, that satisfy certain criteria;

determining a third set of completed queries, wherein the third set of completed queries are completed queries, from the second set, that are most popular; and

the particular completed query is a most popular query from the third set of completed queries.

22. The one or more non-transitory storage media of claim 21 wherein the certain criteria includes that the queries were sent by users that match one or more characteristics of the user that is formulating the search query.

23. The one or more non-transitory storage media of claim 21 wherein the certain criteria includes that the queries were sent at a time that matches a time at which the user that is formulating the search query.

24. The one or more non-transitory storage media of claim 21 wherein the certain criteria includes that the queries were sent from locations that match location information related to the user that is formulating the search query.

Assignments (6)
PATENT SECURITY AGREEMENT (FIRST LIEN) Recorded Sep 29, 2022
From: YAHOO ASSETS LLC
To: ROYAL BANK OF CANADA, AS COLLATERAL AGENT
Reel/Frame 061571/0773 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 16, 2021
From: YAHOO AD TECH LLC (FORMERLY VERIZON MEDIA INC.)
To: YAHOO ASSETS LLC
Reel/Frame 058982/0282 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 26, 2020
From: OATH INC.
To: VERIZON MEDIA INC.
Reel/Frame 054258/0635 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 2, 2018
From: YAHOO HOLDINGS, INC.
To: OATH INC.
Reel/Frame 045240/0310 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 23, 2017
From: YAHOO! INC.
To: YAHOO HOLDINGS, INC.
Reel/Frame 042963/0211 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 25, 2015
From: ZHU, SHENHONG; NAKAO, KAZUHIRO; CHEN, ZHONGQIANG; SZE, CHUN MING; WU, HUMING; MAGHOUL, FARZIN
To: YAHOO! INC.
Reel/Frame 035705/0471 →