Determining a user habit

• US 9,766,998 B1
• Filed: 12/31/2013
• Issued: 09/19/2017
• Est. Priority Date: 12/31/2013
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Sar, Erwin Can, Sohn, Timothy Youngjin, Tomkins, Andrew
• Primary Examiner(s): Gray, David M
• Assistant Examiner(s): Evans, Geoffrey T
• Application Number:
  US14/144,966
• Time in Patent Office: 1,358 Days
• Field of Search: None
• CPC Class Codes: G06F 11/3476 Data logging G06F11/14, G06F11/2205 take precedence
• CPC Class Codes: G06F 16/24575 using context
• CPC Class Codes: G06F 16/90324 using system suggestions
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation

Abstract

Methods and apparatus related to determining one or more user habits for a user. A group of one or more past user activity occurrences of a user may be determined based on similarity between the past user activity occurrences of the group. A user habit may be determined based on the past user activity occurrences of the group.

Claims

1. A computer implemented method, comprising:

identifying a plurality of past activity occurrences of a user, each of the past activity occurrences including an interaction indicator and one or more trigger indicators;

and the interaction indicator for each of the past activity occurrences including at least one of;

one or more user actions and

one or more interaction entities interacted with during the user actions;

determining a group of the past activity occurrences of the user, the group including multiple of the past activity occurrences and determined based on an interaction similarity between the interaction indicators of the past activity occurrences of the group;

determining one or more habit user actions based on the user actions of the group;

determining one or more habit interaction entities based on the interaction entities of the group;

determining habit trigger indicators based on the trigger indicators of the group; and

associating a user habit with the user, the user habit including the habit user actions, the habit interaction entities, and the habit trigger indicators;

receiving user activity data that is based on at least one of;

a location of a computing device of a user, and an action via the computing device;

determining that the user activity data is indicative of one or more of the habit trigger indicators of the user habit; and

based on determining that the user activity data is indicative of one or more of the habit trigger indicators;

providing information that is influenced by the determined user habit, wherein the information is provided;

for display by the computing device or an additional computing device of the user, or

to cause an application to be automatically opened by the computing device or the additional computing device.

2. The method of claim 1, wherein the trigger indicators for the past activity occurrences include one or more temporal indicators associated with the past activity occurrences.

3. The method of claim 2, wherein determining the habit trigger indicators includes determining one or more habit temporal indicators based on the temporal indicators of the group.

4. The method of claim 3, wherein the temporal indicators include temporal indicators related to a time of day.

5. The method of claim 3, wherein the temporal indicators include temporal indicators related to a day of the week.

6. The method of claim 1, further comprising determining the interaction similarity between the interaction indicators of the past activity occurrences of the group based on a user action similarity between the user actions of the group and based on an interaction entity similarity between the interaction entities of the group.

7. The method of claim 6, wherein determining the interaction entity similarity between the interaction entities of the group is based on one or more relationships between the interaction entities.

8. The method of claim 7, wherein the one or more relationships include relationships to one or more entity collections.

9. The method of claim 1, further comprising determining a confidence measure for the user habit based on a count of the past activity occurrences in the group.

10. The method of claim 9, wherein the count of past activity occurrences is a frequency of the past activity occurrences.

11. The method of claim 1, wherein the user actions and the interaction entities of the past activity occurrences are determined based on input from a computing device of the user.

12. The method of claim 1, further comprising:

receiving a partial query provided via the computing device or the additional computing device;

wherein the information that is influenced by the determined user habit is an autocomplete suggestion for the partial query that is promoted based on the user habit, and wherein the autocomplete suggestion is promoted based on being related to one or more of the habit user actions or the habit interaction entities of the user habit; and

wherein providing the information comprises providing the autocomplete suggestion for display in response to the partial query.

13. The method of claim 1, wherein the information that is influenced by the determined user habit is a search result, the search result being promoted based on being related to one or more of the habit user actions or the habit interaction entities of the user habit;

and

wherein providing the information comprises providing the search result for display by the computing device.

14. The method of claim 1, wherein the information is a recommendation that is provided for display and that includes a selectable element that, when selected, automatically populates content in the application of the computing device or the additional computing device, the content being associated with one of the habit interaction entities of the user habit.

15. The method of claim 1, wherein the information is a recommendation that is provided for display and that includes a selectable element that, when selected, automatically dials a phone number for one of the habit interaction entities via the computing device or the additional computing device.

16. The method of claim 1, wherein the information is a command to cause the application to be automatically opened by the computing device or the additional computing device, wherein the application is associated with the habit actions or the habit interaction entities of the user habit.

17. The method of claim 1, wherein the user activity data is based on both the location of the computing device and the action via the computing device;

and wherein determining that the user activity data is indicative of one or more of the habit trigger indicators of the user habit comprises determining that the user activity data is indicative of each of the habit trigger indicators of the user habit.

18. A computer implemented method, comprising:

identifying past activity occurrences of a user, each of the past activity occurrences including;

an action identifier, the action identifier indicative of an action of the user in performing a past user activity;

an interaction entity identifier, the interaction entity identifier indicative of an entity interacted with in performing the past user activity; and

one or more trigger indicators;

determining, for each of the past activity occurrences, an entity collection to which the interaction entity identifier of the past activity occurrence belongs;

determining a group of the past activity occurrences based on the past activity occurrences of the group having at least one communal said entity collection, and the trigger indicators of the past activity occurrences of the group being similar; and

determining a user habit based on the group, the user habit including one or more habit interaction entities based on the communal said entity collection and including one or more habit trigger indicators based on one or more of the trigger indicators of the group;

receiving user activity data that is based on at least one of;

a location of a computing device of a user, and an action via the computing device;

determining actual or anticipated entry of the user into the user habit based on the user activity data indicating one or more of the habit trigger indicators of the user habit; and

based on determining the actual or anticipated entry of the user into the user habit;

providing information based on the information being related to one or more of the habit interaction entities of the user habit, wherein the information is provided;

for display by the computing device or an additional computing device of the user, or

to cause an application to be automatically opened by the computing device or the additional computing device.

19. The method of claim 18, wherein the trigger indicators of each of the past activity occurrences include a trigger indicator indicative of at least one of a location, a time, and a precursor action associated with the user performing the past user activity.

20. The method of claim 18, wherein the habit interaction entities include an identifier of the communal said entity collection.

21. The method of claim 18, wherein determining the habit interaction entities based on the communal said entity collection includes determining a given member of the communal said entity collection as one of the habit interaction entities, wherein the given member is not identified in the group of past activity occurrences of the user.

22. The method of claim 18, further comprising:

determining, for each of the past activity occurrences, an action collection to which the action identifier of the past activity occurrence belongs;

wherein determining the group of past activity occurrences is further based on the past activity occurrences of the group having a communal said action collection; and

wherein the user habit further includes one or more habit actions based on the communal said action collection.

23. The method of claim 18, wherein the information is a recommendation that is provided for display and that includes a selectable element that, when selected, automatically populates content in the application of the computing device or the additional computing device, the content being associated with one of the habit interaction entities of the user habit.