Formulating predicted locations for a mobile device

Patent metadata

Field	Value
Publication number	US-9955312-B2
Application number	US-201615275291-A
Country	US
Kind code	B2
Filing date	Sep 23, 2016
Priority date	Jun 12, 2016
Publication date	Apr 24, 2018
Grant date	Apr 24, 2018

Abstract

Some embodiments of the invention provide a method for displaying a map. The method provides a first display area to display a map, and a second display area to overlap a portion of the first display area to display (i) a field to receive a search parameter and (ii) a set of predicted locations to view on the map. The second display area is moveable over the first display area in order to decrease its size to allow a larger portion of the map to be displayed in the first display area, or to increase its size to allow a larger number of predicted locations to be displayed in the second display area. In some embodiments, the second display area overlaps a bottom portion of the first display area. In some embodiments, the method is implemented by a map application that executes on a mobile device. The set of predicted locations displayed in the second display area in some embodiments include addresses harvested from applications executing on the mobile device. Examples of such applications include electronic mail applications, text messaging applications, the map application, ticket applications, restaurant reservation applications, social media applications, real estate applications, etc. The set of predicted locations includes in some embodiments addresses associated with previous destinations traveled to by the mobile device.

First claim

The invention claimed is:

1. A mobile device comprising a non-transitory storage medium for storing a prediction program for formulating predicted destinations for the mobile device, the program comprising sets of instructions for:
obtaining candidate locations from a plurality of applications executing on the mobile device;
using a first prediction process and a different, second prediction process to formulate respectively a first set of predicted locations based on a current location of the mobile device and for a first location data client and a different, second set of predicted locations based on the current location of the mobile device and for a second location data client; and
providing the first and second sets of predicted locations respectively to the first and second location data clients, both of which execute on the mobile device.

2. The mobile device of claim 1 ,
wherein the first prediction process formulates a first sorted set of predicted locations based on a first set of sorting criteria, while the second prediction process formulates a second sorted set of predicted locations based on a second set of sorting criteria;
wherein the first set of predicted locations for the first data client is different than the second set of predicted locations for the second data client because the first set of sorting criteria for the first data client is different than the second set of sorting criteria for the second client.

3. The mobile device of claim 2 , wherein the two different sorted sets of predicted locations differ because one of the formulated sets of predicted locations has at least one predicted location that is not in the other formulated set of predicted locations.

4. The mobile device of claim 2 , wherein the two different sorted sets of predicted locations differ because at least one predicted location appears at a different position in the sorted order of one set than that predicted location appears in the sorted order of the other formulated set.

5. The mobile device of claim 2 ,
wherein the program further comprises a set of instructions for analyzing a set of attributes associated with the obtained candidate locations in order to identify an initial list of predicted locations;
wherein the first and second prediction processes formulate the first and second sorted sets of predicted locations by using the initial list of predicted locations to generate the first and second sets of predicted locations.

6. The mobile device of claim 5 ,
wherein the first prediction process comprises a set of instructions for limiting the initial list of predicted locations to N predicted locations;
wherein the second prediction process comprises a set of instructions for limiting the initial list of predicted locations to M predicted locations,
wherein N and M are two different integers.

7. The mobile device of claim 5 , wherein the set of instructions for analyzing the set of attributes comprises a set of instructions for filtering out a subset of the obtained candidate locations.

8. The mobile device of claim 5 , wherein the set of instructions for analyzing the set of attributes comprises a set of instructions for filtering out a subset of the obtained candidate locations that are duplicative of other obtained candidate locations.

9. The mobile device of claim 5 , wherein the set of instructions for analyzing the set of attributes comprises sets of instructions for filtering out a subset of the obtained candidate locations;
computing a score for each candidate location that is not filtered out; and
based on the computed scores, sorting the candidate locations that are not filtered out into the initial list of predicted locations,
wherein each of the first and second prediction processes selects a different subset of the list of predicted locations and then sorts the selected subset based on the set of sorting criteria used by the prediction process.

10. The mobile device of claim 5 , wherein the program further comprises a set of instructions for directing a tracking process that executes on the mobile device to maintain travel data for a subset of predicted locations on the initial list.

11. The mobile device of claim 10 , wherein the travel data for a predicted location comprises one of an estimated time of travel to the predicted location and data relating to traffic along a route to the predicted location.

12. A non-transitory machine readable medium for storing a prediction program for formulating predicted destinations for a mobile device, the program comprising sets of instructions for:
obtaining candidate locations from a plurality of applications executing on the mobile device;
using a first prediction process and a different, second prediction process to formulate respectively a first set of predicted locations based on a current location of the mobile device and for a first location data client and a different, second set of predicted locations based on the current location of the mobile device and for a second location data client; and
providing the first and second sets of predicted locations respectively to the first and second location data clients, both of which execute on the mobile device.

13. The non-transitory machine readable medium of claim 12 ,
wherein the first prediction process formulates a first sorted set of predicted locations based on a first set of sorting criteria, while the second prediction process formulates a second sorted set of predicted locations based on a second set of sorting criteria;
wherein the first set of predicted locations for the first data client is different than the second set of predicted locations for the second data client because the first set of sorting criteria for the first data client is different than the second set of sorting criteria for the second client.

14. The non-transitory machine readable medium of claim 13 , wherein the two different sorted sets of predicted locations differ because one of the formulated sets of predicted locations has at least one predicted location that is not in the other formulated set of predicted locations.

15. The non-transitory machine readable medium of claim 13 , wherein the two different sorted sets of predicted locations differ because at least one predicted location appears at a different position in the sorted order of one set than that predicted location appears in the sorted order of the other formulated set.

16. The non-transitory machine readable medium of claim 13 ,
wherein the program further comprises a set of instructions for analyzing a set of attributes associated with the obtained candidate locations in order to identify an initial list of predicted locations;
wherein the first and second prediction processes formulate the first and second sorted sets of predicted locations by using the initial list of predicted locations to generate the first and second sets of predicted locations.

17. The non-transitory machine readable medium of claim 16 ,
wherein the first prediction process comprises a set of instructions for limiting the initial list of predicted locations to N predicted locations;
wherein the second prediction process comprises a set of instructions for limiting the initial list of predicted locations to M predicted locations,
wherein N and M are two different integers.

18. The non-transitory machine readable medium of claim 16 , wherein the set of instructions for analyzing the set of attributes comprises a set of instructions for filtering out a subset of the obtained candidate locations.

Assignees

• Apple Inc

Inventors

• Aerts Tim A

Classifications

• H04W4/028 Primary

  Electricity · mapped topic

• H04W64/00

  Locating users or terminals {or network equipment} for network management purposes, e.g. mobility management · CPC title

• G01C21/3874

  Structures specially adapted for data searching and retrieval · CPC title

• G01C21/362

  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