IP Library › Granted Patent US 9,618,343
Granted Patent B2
US 9,618,343 · App. 14/105,095 · Granted Apr 11, 2017

Predicted travel intent

Inventors: Zachary Adam Kahn (Bellevue, WA); Karan Singh Rekhi (Bellevue, WA); Gautam Kedia (Bellevue, WA)
Assignee: Microsoft Technology Licensing, LLC
G01C21/00G01C21/3484G06F17/30241G06F17/30702G06F17/30867H04W4/021H04W4/206G01C21/3617
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Quick Facts
Patent No.
US 9,618,343
App. No.
14/105,095
Filed
Dec 12, 2013
Granted
Apr 11, 2017
Kind
B2
Art Unit
3669
USPC
701/408
Abstract

One or more techniques and/or systems are provided for providing a recommendation and/or a travel interface based upon a predicted travel intent. For example, a set of user signals (e.g., search queries, calendar information, social network data, etc.) may be evaluated to determine the predicted travel intent for a user to travel to a destination. A recommendation may be provided based upon the predicted travel intent. For example, images, news stories, advertisements, events, attractions, travel accommodation (e.g., hotel, car, and/or flight reservation functionality) and/or other information and functionality associated with the destination may be provided through the recommendation. The recommendation may be provided through an alert, a mobile app, a website, a travel interface, and/or a variety of other interfaces. The predicted travel intent may be used to modify information provided by a website, an operating system, and/or apps (e.g., a news app may display information about the destination).

Claims (93)

1. A method for providing a recommendation for a travel destination, comprising:

evaluating a set of historical user location data associated with a device of the user to determine a location of a first user hub;

evaluating a set of user signals associated with a user to identify a potential travel destination and a future travel date;

determining a travel distance to the potential travel destination based on the location of the first user hub;

determining the travel distance exceeds a predetermined threshold distance; and

based on the travel distance exceeding the predetermined threshold distance, determining the predicted travel intent for the user to travel to the potential destination; and providing a recommendation based upon the potential destination and the future travel date.

2. The method of claim 1 , wherein determining the predicted travel intent further comprises evaluating a set of user signals comprising:

locational information associated with a device of the user.

3. The method of claim 1 , wherein determining the predicted travel intent further comprises evaluating a set of user signals comprising:

search query history associated with the user.

4. The method of claim 3 , wherein the search query history comprises at least one of:

a flight search query;

a hotel search query;

a location search query;

an attraction search query;

a business search query; or

an event search query.

5. The method of claim 1 , wherein determining the predicted travel intent further comprises evaluating a set of user signals comprising at least one of:

a message associated with the user;

a phone number called by the user;

a social network post;

user browsing history;

content marked by the user through a social network;

a calendar entry; or

user created data.

6. The method of claim 1 , wherein providing a recommendation further comprises:

displaying the recommendation through at least one of an operating system welcome screen, an operating system user interface, a mobile app, a website, a search engine homepage, or a carousel interface.

7. The method of claim 1 , wherein providing a recommendation further comprises:

identifying a user interface comprising a set of information interfaces; and

selectively replacing at least one information interface of the set of information interfaces with the recommendation.

8. The method of claim 1 , wherein the recommendation comprises at least one of:

a photo, extracted from a social network, associated with the destination;

an image associated with the destination;

a news story associated with the destination;

an event at the destination;

an advertisement for a business associated with the destination;

a website link to a web site;

an app link to a mobile app;

a social network link to a social network profile of an entity associated with the destination;

an attraction at the destination; or

travel task completion information.

9. The method of claim 1 , further comprising:

providing a travel interface populated with the recommendation.

10. The method of claim 9 , further comprising:

populating the travel interface with a confirmable question as to whether the predicted travel intent is correct.

11. The method of claim 9 , further comprising:

populating the travel interface with at least one of:

weather information for the destination;

an attraction interface for the destination, the attraction interface comprising at least one of an attraction name, an attraction description, or an attraction image;

a travel accommodation interface for the destination, the travel accommodation interface comprising at least one of a travel accommodation name, a travel accommodation description, or a travel accommodation image;

a selectable interest interface associated with an interest;

a travel date input interface;

a travel route planning interface;

a configuration interface; or

a supplemental information interface.

12. The method of claim 1 , further comprising:

evaluating the set of user signals to identify a set of potential travel locations;

performing clustering relative to the set of potential travel locations to create a location cluster, the location cluster comprising two or more potential travel locations of the set of potential travel locations; and

identifying the potential travel destination based upon the location cluster, the potential travel destination corresponding to one or more potential travel locations within the location cluster.

13. The method of claim 1 , further comprising:

utilizing a global approximate travel timeline to determine the future travel date; and

tailoring the recommendation based upon the future travel date.

14. The method of claim 1 , further comprising:

evaluating the set of historical user location data associated with the device of the user to determine a location of a second user hub; and

wherein determining the travel distance to the potential travel destination is further based on the location of the second user hub.

15. The method of claim 1 , wherein determining the predicted travel intent further comprises utilizing a classifier and a travel training dataset to assign an intent to travel score to the potential destination above a travel threshold.

16. A system for providing a recommendation based upon a predicted travel intent, comprising:

at least one processor;

a memory storing instructions that are configured to, when executed by the at least one processor, perform the following actions:

evaluate a set of historical user location data associated with a device of the user to determine a location of a user hub;

evaluate a set of user signals associated with a user to identify a potential travel destination and a future travel date;

determine a travel distance to the potential travel destination based on the location of the first user hub; and

if the travel distance exceeds a predetermined threshold distance, provide a recommendation based upon the potential destination and the future travel date.

17. The system of claim 16 , wherein the actions further comprise:

provide a travel interface populated with the recommendation; and

populate the travel interface with at least one of:

weather information for the destination;

an attraction interface for the destination, the attraction interface comprising at least one of an attraction name, an attraction description, or an attraction image;

a travel accommodation interface for the destination, the travel accommodation interface comprising at least one of a travel accommodation name, a travel accommodation description, or a travel accommodation image;

a selectable interest interface associated with an interest;

a travel date input interface;

a travel route planning interface;

a configuration interface; or

a supplemental information interface.

18. The system of claim 16 , the actions further comprising:

display the recommendation through at least one of an operating system welcome screen, an operating system user interface, a mobile app, a website, a search engine homepage, or a carousel interface.

19. A device comprising instructions that when executed perform a method for displaying a travel interface comprising:

evaluating a set of historical user location data associated with a device of the user to determine a location of a user hub;

evaluating a set of user signals associated with a user to identify a destination and a future travel date;

identifying a predicted travel intent for a user to travel to the potential destination based on a distance from the user hub to the destination exceeding a predetermined threshold;

generating a travel interface populated with one or more recommendations associated with the destination and the future travel date, a recommendation comprising at least one of an image, weather information, attraction information, event information, an advertisement, a news story, or travel task completion information associated with the destination; and

displaying the travel interface through at least one of an operating system user interface, a mobile app, or a website.

20. The device of claim 19 , wherein the user signals include a social network post and the recommendation includes a social media photo.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 9, 2015
From: MICROSOFT CORPORATION
To: MICROSOFT TECHNOLOGY LICENSING, LLC
Reel/Frame 039025/0454 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 12, 2013
From: KAHN, ZACHARY ADAM; REKHI, KARAN SINGH; KEDIA, GAUTAM
To: MICROSOFT CORPORATION
Reel/Frame 031776/0323 →
Continuity (1)
Related Publication 20150168150A1 · Jun 18, 2015