Predicted travel intent

• US 9,976,864 B2
• Filed: 04/07/2017
• Issued: 05/22/2018
• Est. Priority Date: 12/12/2013
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Kahn, Zachary Adam, Rekhi, Karan Singh, Kedia, Gautam
• Primary Examiner(s): Melton, Todd
• Application Number:
  US15/482,185
• Publication Number:
  US 20170211945A1
• Time in Patent Office: 410 Days
• Field of Search: None
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G01C 21/3617 using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement
• CPC Class Codes: G06F 16/29 Geographical information databases
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
• CPC Class Codes: G06F 16/955 using information identifiers, e.g. uniform resource locators [URL]
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/04 Inference or reasoning models
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/21 for social networking applications

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

1. A computer-implemented method for generating a travel interface, the method comprising:

evaluating a set of user signals associated with a user to identify a plurality of potential travel locations;

clustering the potential travel locations to create a location cluster, the location cluster comprising two or more potential travel locations of the plurality of potential travel locations;

identifying a travel destination based upon the location cluster; and

providing a recommendation based upon the potential destination.

2. The computer-implemented method of claim 1, wherein the set of user signals includes at least search query history associated with the user.

3. The computer-implemented method of claim 2, wherein the search query history includes 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.

4. The computer-implemented method of claim 1, wherein the set of user signals includes 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.

5. The computer-implemented method of claim 1, further comprising determining a future travel date for traveling to the travel destination.

6. The computer-implemented method of claim 1, wherein providing the recommendation includes 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, and wherein the recommendation includes 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.

7. The computer-implemented method of claim 1, wherein identifying a travel destination further comprises utilizing a classifier and a travel training dataset to assign an intent to travel score to a potential travel destination above a travel threshold.

8. The computer-implemented method of claim 1, wherein the potential travel locations include attractions within a city, and the travel destination is the city.

9. A system 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;

evaluating a set of user signals associated with a user to identify a plurality of potential travel locations;

clustering the potential travel locations to create a location cluster, the location cluster comprising two or more potential travel locations of the plurality of potential travel locations;

identifying a travel destination based upon the location cluster; and

providing a recommendation based upon the potential destination.

10. The system of claim 9, wherein the set of user signals includes at least search query history associated with the user.

11. The system of claim 9, wherein the search query history includes 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.

12. The system of claim 9, wherein the recommendation includes at least three 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.

13. The system of claim 9, wherein the plurality of travel locations includes at least three travel locations.

14. The system of claim 9, wherein the user signals include a social network post and the recommendation includes a social media photo.

15. A device storing instructions that when executed perform a method comprising:

displaying a travel interface having a plurality of sections;

evaluating search query history of a user to identify a plurality of potential travel locations, wherein the potential travel locations include at least one of a hotel, an attraction, a business, or an event;

clustering the potential travel locations to create a location cluster, the location cluster comprising two or more potential travel locations of the plurality of potential travel locations;

identifying a travel destination based upon the location cluster; and

populating the plurality of sections of the travel interface with recommendations based on the identified travel destination.

16. The device of claim 15, wherein the recommendations include at least two 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.

17. The device of claim 15, wherein the potential travel locations are within a city, and the travel destination is the city.

18. The device of claim 15, wherein identifying a travel destination further comprises utilizing a classifier and a travel training dataset to assign an intent to travel score to a potential travel destination above a travel threshold.

19. The device of claim 15, wherein the travel interface includes 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;

or

a travel route planning interface.

20. The device of claim 15, wherein identifying a travel destination is further based on locational information associated with a device of the user.