INTELLIGENT DESTINATION RECOMMENDATIONS BASED ON HISTORICAL DATA

• US 20130238241A1
• Filed: 03/09/2012
• Published: 09/12/2013
• Est. Priority Date: 03/09/2012
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Chelotti, Brandon Anthony, Miller, Howard Aron, Strathmeier, Brian Egon
• Granted Patent: US 9,200,918 B2
• Time in Patent Office: Days
• US Class Current: 701/533
• 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: G01C 21/362 received from an external device or application, e.g. PDA, mobile phone or calendar application
• CPC Class Codes: G06Q 10/109 Time management, e.g. calendars, reminders, meetings or time accounting

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.

Claims

1. A machine-implemented method comprising:

determining, by a processing device, an estimated mode of transportation;

calculating, by the processing device, confidence ratings for one or more destinations based on the estimated mode of transportation and processing device travel history; and

selecting, by the processing device, a destination based upon a confidence rating.

2. The machine-implemented method of claim 1, wherein the calculating 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 2, wherein the calculating confidence ratings further comprises determining one or more of:

frequency of visits to a destination, current location, path of travel, and user overrides.

4. The machine-implemented method of claim 1, further comprising:

displaying the selected destination in a manner that a user can accept or reject the selected destination;

receiving input accepting the selected destination; and

determining a route to the selected destination from a current location.

5. The machine-implemented method of claim 1, further comprising:

determining the determined route was rejected;

adjusting the confidence rating for the selected destination; and

displaying a list of destinations ranked in order based upon their confidence ratings.

6. The machine-implemented method of claim 1, wherein the stored destination data is based upon determining a location of the processing device.

7. The machine-implemented method of claim 6, wherein a frequency of the determining a location of the processing device is adjusted based on movement of the processing device.

8. The machine-implemented method of claim 6, further comprising:

storing the determined locations; and

storing a time associated with each determined location.

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

10. The machine-implemented method of claim 9, further comprising:

storing locations associated with calendar entries; and

storing a time associated with each location associated with a calendar entry.

11. The machine-implemented method of claim 10, wherein the displaying the selected destination is triggered by the user opening a navigation application.

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 processing 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 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 the selected 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 selected destination.

18. The machine-implemented method of claim 1, wherein the mode of transportation is determined by analyzing the movement of the processing device to.

19. The machine-implemented method of claim 1, wherein the 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. A machine-implemented method comprising:

calculating, by the processing device, confidence ratings for one or more destinations, wherein each destination has a confidence rating and the confidence rating is based on a match between a time and time data for each destination;

selecting, by the processing device, a stored destination based upon a confidence rating; and

creating, by the processing device, a calendar event for the time based upon the selected destination.

22. The machine-implemented method of claim 21, further comprising:

displaying the calendar event in a manner that a user can accept or reject the calendar event as a scheduled calendar event.

23. The machine-implemented method of claim 21, wherein the calendar event is stored as tentative entry in the calendar.

24. The machine-implemented method of claim 21, wherein the calendar event is shared with a plurality of subscribers.

25. The machine-implemented method of claim 21, wherein the one or more destinations and time data are determined from calendar data.

26. A data processing device comprising:

a processor;

a storage device coupled to the processor and configurable for storing instructions, which, when executed by the processor cause the processor to;

determine an estimated mode of transportation;

calculate confidence ratings for one or more destinations, wherein each destination has a confidence rating and the confidence rating is based on a match between a time and time data for each destination;

adjust the confidence rating based on the estimated mode of transportation; and

select a stored destination based upon a confidence rating; and

display the selected destination in a manner that a user can accept or reject the selected destination, wherein the display of the selected destination is triggered by the confidence rating for the selected destination being greater than a threshold value.

27. A data processing device of claim 26, wherein the stored destination data is based upon determining a location of the processing device.

28. A data processing device of claim 26, wherein the processor is further configured to:

store the determined locations; and

store a time associated with each determined location.

29. A data processing device of claim 28, wherein the mode of transportation is determined by analyzing the movement of the processing device to.

30. A data processing device comprising:

a processor;

a storage device coupled to the processor and configurable for storing instructions, which, when executed by the processor cause the processor to;

calculate confidence ratings for one or more destinations, wherein each destination has a confidence rating and the confidence rating is based on a match between a time and time data for each destination;

select a stored destination based upon a confidence rating; and

create a calendar event for the time based upon the selected destination.

31. A data processing device of claim 30, wherein the processor is further configured to:

recognize a vehicle from a connection history between the processing device and the vehicle; and

select a connection mode to the vehicle based on the connection history.

32. A machine readable non-transitory storage medium containing executable program instructions which cause a data processing device to perform a method comprising:

calculating, by the processing device, confidence ratings for one or more destinations based on a match between a time and time data for each destination;

selecting, by the processing device, a stored destination based upon a confidence rating; and

displaying the selected destination in a manner that a user can accept or reject the selected destination.

33. The machine-implemented method of claim 32, wherein the displaying the selected destination is triggered by the processing device detecting a proximity to a mode of transportation

34. The machine-implemented method of claim 32, further comprising:

receiving input accepting the selected destination; and

determining a route to the selected destination from a current location.

35. The machine-implemented method of claim 32, further comprising:

presenting the user with an option to display a map of the determined route.

36. The machine-implemented method of claim 32, further comprising:

determining the determined route was rejected;

adjusting the confidence rating for the selected destination; and

displaying a list of destinations ranked in order based upon their confidence ratings.

37. A machine readable non-transitory storage medium containing executable program instructions which cause a data processing device to perform a method comprising:

calculating, by the processing device, confidence ratings for one or more destinations, wherein each destination has a confidence rating and a confidence rating is based on a match between a time and time data for each destination;

selecting, by the processing device, a stored destination based upon a confidence rating; and

displaying the selected destination in a manner that a user can accept or reject the selected destination; and

creating, by the processing device, a calendar event for the time based upon the selected destination.

38. The machine-implemented method of claim 37, further comprising:

displaying the calendar event in a manner that a user can accept or reject the calendar event as a scheduled calendar event.

39. The machine-implemented method of claim 37, wherein the calendar event is stored as tentative entry in the calendar.

40. The machine-implemented method of claim 37, wherein the calendar event is shared with a plurality of subscribers.

41. The machine-implemented method of claim 37, wherein the one or more destinations and time data are determined from calendar data.

42. An apparatus comprising:

means for determining an estimated mode of transportation;

means for calculating confidence ratings for one or more destinations, wherein each destination has a confidence rating and the confidence rating is based on a match between a time and time data for each destination;

means for adjusting the confidence rating based on the estimated mode of transportation; and

means for selecting a stored destination based upon a confidence rating; and

means for displaying the selected destination in a manner that a user can accept or reject the selected destination.

43. An apparatus comprising:

means for calculating confidence ratings for one or more destinations, wherein each destination has a confidence rating and a confidence rating is based on a match between a time and time data for each destination;

means for selecting a stored destination based upon a confidence rating; and

means for displaying the selected destination in a manner that a user can accept or reject the selected destination; and

means for creating a calendar event for the time based upon the selected destination.