Server computing device for recommending meeting a friend at a service location based on current location, travel direction, and calendar activity

Patent metadata

Field	Value
Publication number	US-9569726-B2
Application number	US-201615059714-A
Country	US
Kind code	B2
Filing date	Mar 3, 2016
Priority date	Jun 30, 2011
Publication date	Feb 14, 2017
Grant date	Feb 14, 2017

Abstract

A server computing device and related method for providing recommendations to a user computing device are disclosed. In one example, user activity of the user of a user computing device and friend activity of a friend using a friend computing device are received. A request for a recommendation is received from the user device. Based on the user and friend activities, it is estimated that the user and friend will approach an intersecting location within a window of time, and the user and friend are available to meet in that window. A recommendation of a service offered within a distance of the location is sent, with the recommendation displayed on the user computing device.

First claim

The invention claimed is:

1. A server computing device for providing recommendations to a user computing device, the server computing device comprising:
a processor configured to:
receive user activity including a detected current location of and direction of travel of the user computing device and calendar activity of a user of the user computing device;
receive friend activity of a friend using a friend computing device, the friend activity including a detected current location of and direction of travel of the friend computing device and calendar activity of the friend, and to receive from the user computing device a request for a recommendation for a target product or service;
estimate that the user and the friend will approach an intersecting location within a predetermined window of time, based on the respective detected current locations and directions of travel of the user computing device and the friend computing device;
determine that the user and the friend are available to meet in the predetermined window of time based on the calendar activity of the user and the calendar activity of the friend; and
send the recommendation including a recommended service offered at a service location within a threshold distance of the intersecting location, wherein the recommendation is displayed on a display associated with the user computing device, the recommendation facilitating a meeting between the user and the friend.

2. The server computing device of claim 1 , wherein the processor is further configured to receive from the user computing device one or more user recommendation preferences indicating product or service recommendations that the user would like to receive from the server computing device, and the processor is further configured to utilize the one or more user recommendation preferences to determine the recommendation.

3. The server computing device of claim 2 , wherein the processor is further configured to make an inference that a trigger condition for at least one of the one or more user recommendation preferences will arise, wherein the inference is based on the detected current location of the user, a behavioral pattern of the user, and one or more contextual factors associated with current observed user activity.

4. The server computing device of claim 3 , wherein the one or more contextual factors includes a date, a day of a week, a time of day, or a time period that the user computing device has been in the detected current location.

5. The server computing device of claim 3 , wherein the trigger condition comprises a future location of the user.

6. The server computing device of claim 1 , wherein the user activity comprises user activity with a plurality of computer programs that are monitored according to a user authorization.

7. The server computing device of claim 6 , wherein the processor is further configured to dynamically monitor the user activity by selectively activating or accessing at least one of the plurality of computer programs based on computing an expected value of information that is gleaned from the user activity.

8. The server computing device of claim 1 , wherein the user activity comprises a sharing-authorized category of activity that the user authorizes a personal agent program of the user computing device to send to the server computing device with the request for the recommendation.

9. The server computing device of claim 1 , wherein the processor is further configured to:
generate aggregate behavioral patterns from observing a user population over time;
examine the user activity for user activity that matches the aggregate behavioral patterns within a threshold degree; and
based on the user activity that matches the aggregate behavioral patterns within a threshold degree, learn a behavioral pattern of the user.

10. The server computing device of claim 9 , wherein the processor is further configured to create a user recommendation preference based on the behavioral pattern of the user.

11. A method for providing recommendations to a user computing device, the method comprising:
receiving user activity including a detected current location of and direction of travel of the user computing device and calendar activity of a user of the user computing device;
receiving friend activity of a friend using a friend computing device, the friend activity including a detected current location of and direction of travel of the friend computing device and calendar activity of the friend;
receiving from the user computing device a request for a recommendation for a target product or service;
estimating that the user and the friend will approach an intersecting location within a predetermined window of time, based on the respective detected current locations and directions of travel of the user computing device and the friend computing device;
determining that the user and the friend are available to meet in the predetermined window of time based on the calendar activity of the user and the calendar activity of the friend; and
sending the recommendation including a recommended service offered at a service location within a threshold distance of the intersecting location, wherein the recommendation is displayed on a display associated with the user computing device, the recommendation facilitating a meeting between the user and the friend.

12. The method of claim 11 , further comprising:
receiving from the user computing device one or more user recommendation preferences indicating product or service recommendations that the user would like to receive; and
utilizing the one or more user recommendation preferences to determine the recommendation.

13. The method of claim 12 , further comprising making an inference that a trigger condition for at least one of the one or more user recommendation preferences will arise, wherein the inference is based on the detected current location of the user, a behavioral pattern of the user, and one or more contextual factors associated with current observed user activity.

14. The method of claim 13 , wherein the one or more contextual factors includes a date, a day of a week, a time of day, or a time period that the user computing device has been in the detected current location.

15. The method of claim 13 , wherein the trigger condition comprises a future location of the user.

16. The method of claim 11 , wherein the user activity comprises user activity with a plurality of computer programs that are monitored according to a user authorization.

17. The method of claim 16 , further comprising dynamically monitoring the user activity by selectively activating or accessing at least one of the plurality of computer programs based on computing an expected value of information that is gleaned from the user activity.

18. The method of claim 11 , wherein the user activity comprises a sharing-authorized category of activity that the user authorizes a personal agent program of the user computing device to send to a server computing device with the request for the recommendation.

19. The method of claim 11 , further comprising:
generating aggregate behavioral patterns from observing a user population over time;
examining the user activity for user activity that matches the aggregate behavioral patterns within a threshold degree; and
based on the user activity that matches the aggregate behavioral patterns within a threshold degree, learning a behavioral pattern of the user.

20. A method for providing recommendations to a user computing device,

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Horvitz Eric
• Paparizos Stelios
• Barga Roger
• Burger Doug
• Gupta Vinay

Classifications

• G06N5/022 Primary

  Knowledge engineering; Knowledge acquisition · CPC title

• G06Q30/02

  Marketing; Price estimation or determination; Fundraising · CPC title

• G01C21/3679

  Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities (G01C21/3611 takes precedence) · CPC title

• G06N5/04 Primary

  Inference or reasoning models · CPC title

• G06N99/005

  Physics · mapped topic