Intelligent destination recommendations based on historical data

Patent metadata

Field	Value
Publication number	US-9200918-B2
Application number	US-201213416927-A
Country	US
Kind code	B2
Filing date	Mar 9, 2012
Priority date	Mar 9, 2012
Publication date	Dec 1, 2015
Grant date	Dec 1, 2015

Abstract

Apparatuses and methods relating to navigation and calendar integration are described. In one implementation, confidence ratings are calculated for one or more destinations. Each destination has an associated confidence rating and confidence ratings are based on a match between the current time and time data for each destination. A destination is selected based on confidence rating and displayed. A calendar event is created based upon the selected destination.

First claim

What is claimed is:

1. A machine-implemented method comprising:
determining, by a mobile device, a current location of the mobile device and an estimated mode of transportation, the estimated mode of transportation being a current mode of transportation;
calculating, by the mobile device, respective confidence ratings for one or more destinations, wherein the respective confidence ratings for the one or more destinations are calculated based at least in part on the estimated mode of transportation and travel history of the mobile device, wherein calculating the respective confidence ratings for the one or more destinations includes:
determining a frequency of visits to a destination over a time period and increasing a confidence rating for the destination when one or more timestamps associated with the destination matches a current time;
accessing a transportation profile, wherein the transportation profile stores associations between modes of transportation and previously visited destinations, the transportation profile including an association between the estimated mode and one or more previously visited destinations; and
increasing a first confidence rating for a first destination in the one or more destinations when the transportation profile indicates that the first destination corresponds to a previously visited destination associated with the estimated mode of transportation, the increase relative to a second confidence rating for a second destination in the one or more destinations that is not associated with the estimated mode of transportation;

selecting, by the mobile device, a stored destination based upon a calculated confidence rating, the stored destination being a predicted destination of a user of the mobile device;
displaying the selected destination in a manner that the user can accept or reject the selected destination;
determining if the selected destination was rejected;
adjusting, based on the rejection, the confidence rating for the selected destination; and displaying another destination based upon its confidence rating.

2. The machine-implemented method of claim 1 wherein calculating the respective confidence ratings further comprises determining a match between a current time and a time associated with a destination.

3. The machine-implemented method of claim 1 wherein calculating the respective confidence ratings further comprises determining a current location of the mobile device, a current path of travel, and user overrides.

4. The machine-implemented method of claim 3 wherein a frequency in determining a current location of the mobile device is adjusted based on movement of the mobile device.

5. The machine-implemented method of claim 1 further comprising:
receiving input accepting the stored destination; and
determining a route to the stored destination from the current location.

6. The machine-implemented method of claim 1 further comprising:
determining if a route to the selected destination from the current location was rejected;
adjusting the confidence rating for the selected destination; and
displaying a list of destinations ranked in order based upon their confidence ratings.

7. The machine-implemented method of claim 1 further comprising:
determining one or more locations of the mobile device, wherein the stored destination is selected further based upon the one or more locations of the mobile device.

8. The machine-implemented method of claim 7 further comprising:
storing the one or more determined locations; and
storing a time associated with each determined location.

9. The machine-implemented method of claim 1 wherein the stored destination is selected further based upon calendar data.

10. The machine-implemented method of claim 9 further comprising:
storing one or more locations associated with one or more calendar appointments; and
storing a time associated with each location associated with a calendar appointment.

11. The machine-implemented method of claim 10 further comprising:
displaying the selected destination, wherein the display of the stored destination is triggered when a navigation application has been launched.

12. The machine-implemented method of claim 1 further comprising:
routing directions to the selected destination.

13. The machine-implemented method of claim 1 further comprising:
recognizing a vehicle from a connection history between the mobile device and the vehicle; and
selecting a connection mode to the vehicle based on the connection history.

14. The machine-implemented method of claim 1 wherein the estimated mode of transportation is determined to be one of: pedestrian, vehicle, or mass transportation.

15. The machine-implemented method of claim 14 wherein the determination that transportation is walking is based upon one or more of: travel along known walking routes, input from an accelerometer, and input from a pedometer.

16. The machine-implemented method of claim 14 further comprising:
determining that the stored destination is beyond a historical walking range; and
displaying a recommendation to switch to an alternate mode of transportation.

17. The machine-implemented method of claim 16 further comprising:
retrieving a mass transportation schedule for the current time and the stored destination.

18. The machine-implemented method of claim 1 wherein the estimated mode of transportation is determined by analyzing a movement of the mobile device.

19. The machine-implemented method of claim 1 wherein the estimated mode of transportation is determined to be pedestrian and current weather information is displayed.

20. The machine-implemented method of claim 1 wherein the confidence rating for each destination is based upon one or more of a time of day, a day of a week, or a day of a month.

21. The method of claim 1 wherein the travel history of the mobile device includes travel history of the user of the mobile device, and wherein the destination is associated with the estimated mode of transportation in accordance with the travel history of the mobile device when the travel history and the transportation profile indicate that the destination is a previously visited destination that has been reached using the estimated mode of transportation or when the destination is within a corresponding distance associated with the estimated mode of transportation as indicated by the travel history.

22. The method of claim 1 , further comprising:
accessing the transportation profile to determine an associated distance for the estimated mode of transportation, the associated distance representing a historical distance traveled using the estimated mode of transportation; and
determining a current location of the mobile device, wherein the respective confidence ratings for the one or more destinations are calculated based at least in part upon a comparison between the associated distance and one or more distances between the current location of the mobile device and the one or more destinations.

23. A machine-implemented method comprising:
calculating, by a processing device, respective confidence ratings for one or more destinations;
selecting a stored destination based upon the respective confidence ratings, wherein the stored destination is associated with one or more timestamps;
determining whether the stored destination meets a criteria for adding the stored destination as a calendar appointment, wherein determining whether the s

Assignees

• Chelotti Brandon Anthony
• Miller Howard Aron
• Strathmeier Brian Egon
• Apple Inc

Inventors

• Chelotti Brandon Anthony
• Miller Howard Aron
• Strathmeier Brian Egon

Classifications

• G06Q10/109

  Time management, e.g. calendars, reminders, meetings or time accounting · CPC title

• G01C21/362 Primary

  received from an external device or application, e.g. PDA, mobile phone or calendar application · CPC title

• G01C21/3617

  using user history, behaviour, conditions or preferences, e.g. predicted or inferred from previous use or current movement · CPC title