NAVIGATION SYSTEM HAVING POINT OF INTEREST RECOMMENDATION MECHANISM AND METHOD OF OPERATION THEREOF

• US 20140095063A1
• Filed: 09/28/2012
• Published: 04/03/2014
• Est. Priority Date: 09/28/2012
• Status: Active Grant

• Current Assignee: TeleNav Incorporated
• Original Assignee: TeleNav Incorporated
• Inventors: Saraswat, Meenakshi
• Granted Patent: US 9,874,453 B2
• Time in Patent Office: Days
• US Class Current: 701/410
• CPC Class Codes: G01C 21/3484 Personalized, e.g. from learned user behaviour or user-defined profiles
• CPC Class Codes: G06Q 10/047 Optimisation of routes or paths, e.g. travelling salesman problem
• CPC Class Codes: G06Q 30/0224 based on user history
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0261 based on user location
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

A method of operation of a navigation system includes: monitoring a purchase history; extrapolating a selection behavior associated with the purchase history; extrapolating a group behavior for a member designation associated with the selection behavior; generating a recommendation based on the group behavior; and generating a notification with the recommendation for displaying on a device.

Claims

1. A method of operation of a navigation system comprising:

monitoring a purchase history;

extrapolating a selection behavior associated with the purchase history;

extrapolating a group behavior for a member designation associated with the selection behavior;

generating a recommendation based on the group behavior; and

generating a notification with the recommendation for displaying on a device.

2. The method as claimed in claim 1 wherein generating the recommendation includes:

identifying a current location of the device;

identifying a proximate destination associated with the group behavior; and

further comprising;

generating a route from the current location to the proximate destination.

3. The method as claimed in claim 1 further comprising:

extrapolating a health condition from the purchase history; and

wherein;

generating the recommendation based on the health condition.

4. The method as claimed in claim 1 further comprising:

assigning a weight to each of a plurality of a preference option based on the group behavior of the member designation; and

wherein;

generating the recommendation includes selecting from the plurality of the preference option based on the weight.

5. The method as claimed in claim 1 further comprising:

extrapolating a group specific behavior based on the selection behavior of the member designation; and

wherein;

generating the recommendation includes generating the recommendation based on the group specific behavior.

6. A method of operation of a navigation system comprising:

monitoring a purchase history;

extrapolating a selection behavior associated with the purchase history;

extrapolating a group behavior for a member designation associated with the selection behavior;

extrapolating a plurality of a preference option based on the group behavior;

selecting a recommendation from the plurality of the preference option; and

generating a notification with the recommendation for displaying on a device.

7. The method as claimed in claim 6 further comprising:

receiving a preference request; and

modifying a weight of the preference option based on the preference request; and

wherein;

selecting the recommendation is based on the weight of the preference option.

8. The method as claimed in claim 6 wherein identifying the selection behavior includes identifying a variety preference.

9. The method as claimed in claim 6 wherein identifying the selection behavior includes identifying a user'"'"'s demographic.

10. The method as claimed in claim 6 wherein identifying the selection behavior includes:

identifying a discount preference associated with the group behavior; and

modifying a weight of the preference option based on the discount preference.

11. A navigation system comprising:

a monitor module for monitoring a purchase history;

a behavior module, coupled to the monitor module, for extrapolating a selection behavior associated with the purchase history;

an option module, coupled to the behavior module, for extrapolating a group behavior for a member designation associated with the selection behavior;

a recommendation module, coupled to the option module, for generating a recommendation based on the group behavior; and

a notification module, coupled to the recommendation module, for generating a notification with the recommendation for displaying on a device.

12. The system as claimed in claim 11 further comprising:

a location module, coupled to the monitor module, for identifying a current location of the device;

a destination module, coupled to the location module, for identifying a proximate destination associated with the group behavior; and

a navigation module, coupled to the destination module, for generating a route from the current location to the proximate destination.

13. The system as claimed in claim 11 wherein:

the behavior module is for extrapolating a health condition from the purchase history; and

the recommendation module is for generating the recommendation based on the health condition.

14. The system as claimed in claim 11 wherein:

the option module is for assigning a weight to each of a plurality of a preference option based on the group behavior of the member designation; and

the recommendation module is for generating the recommendation from the plurality of the preference option based on the weight.

15. The system as claimed in claim 11 wherein:

the option module is for extrapolating a group specific behavior based on the selection behavior of the member designation; and

the recommendation module is for generating the recommendation based on the group specific behavior.

16. The system as claimed in claim 11 wherein:

the option module is for extrapolating a plurality of a preference option based on the group behavior; and

the recommendation module is for selecting the recommendation from the plurality of the preference option.

17. The system as claimed in claim 16 further comprising:

a request module, coupled to the monitor module, for receiving a preference request;

a modification module, coupled to the request module, for modifying a weight of the preference option based on the preference request; and

wherein;

the recommendation module is for selecting the recommendation based on the weight of the preference option.

18. The system as claimed in claim 16 wherein the behavior module is for identifying a variety preference.

19. The system as claimed in claim 16 wherein the behavior module is for identifying a user'"'"'s demographic.

20. The system as claimed in claim 16 wherein:

the behavior module is for identifying a discount preference associated with the group behavior; and

further comprising;

a modification module, coupled to the behavior module, for modifying a weight of the preference option based on the discount preference.