Navigation system having point of interest recommendation mechanism and method of operation thereof

• US 9,874,453 B2
• Filed: 09/28/2012
• Issued: 01/23/2018
• Est. Priority Date: 09/28/2012
• Status: Active Grant

• Current Assignee: TeleNav Incorporated
• Original Assignee: TeleNav Incorporated
• Inventors: Saraswat, Meenakshi
• Primary Examiner(s): PATEL, SHARDUL D
• Application Number:
  US13/631,639
• Publication Number:
  US 20140095063A1
• Time in Patent Office: 1,943 Days
• Field of Search: 701400, 701410, 4554143, 705 141
• 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 from an association rule based on a confidence percentage of the association rule, wherein the association rule is determined by;

identifying patterns between purchases in the purchase history and geographic locations of the purchases determined with a global positioning system of a device associated with the purchases; and

tracking the frequency of occurrences between the purchases and the geographic locations;

extrapolating a group behavior for a member designation associated with the selection behavior, the group behavior for identifying a pattern applicable across multiple participants corresponding to the member designation;

generating a recommendation based on the group behavior; and

generating a notification with the recommendation using a control unit for displaying on the 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 from an association rule based on a confidence percentage of the association rule, wherein the association rule is determined by;

identifying patterns between purchases in the purchase history and geographic locations of the purchases determined with a global positioning system of a device associated with the purchases; and

tracking the frequency of occurrences between the purchases and the geographic locations;

extrapolating a group behavior for a member designation associated with the selection behavior, the group behavior for identifying a pattern applicable across multiple participants corresponding to the member designation;

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 using a control unit for displaying on the device.

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

receiving a preference request;

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 control unit configured to;

monitor a purchase history;

extrapolate a selection behavior from an association rule based on a confidence percentage of the association rule, wherein the association rule is determined by;

identifying patterns between purchases in the purchase history and geographic locations of the purchases determined with a global positioning system of a device associated with the purchases; and

tracking the frequency of occurrences between the purchases and the geographic locations;

extrapolate a group behavior for a member designation associated with the selection behavior, the group behavior for identifying a pattern applicable across multiple participants corresponding to the member designation;

generate a recommendation based on the group behavior;

generate a notification with the recommendation; and

a communication unit, coupled to the control unit, configured to communicate the notification with the recommendation.

12. The system as claimed in claim 11 wherein the control unit is configured to:

identify a current location of the device;

identify a proximate destination associated with the group behavior; and

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

13. The system as claimed in claim 11 wherein the control unit is configured to:

extrapolate a health condition from the purchase history;

and

generate the recommendation based on the health condition.

14. The system as claimed in claim 11 wherein the control unit is configured to:

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

generate the recommendation from the plurality of the preference option based on the weight.

15. The system as claimed in claim 11 wherein the control unit is configured to:

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

generate the recommendation based on the group specific behavior.

16. The system as claimed in claim 11 wherein the control unit is configured to:

extrapolate a plurality of a preference option based on the group behavior; and

select the recommendation from the plurality of the preference option.

17. The system as claimed in claim 16 wherein the control unit is configured to:

receive a preference request;

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

select the recommendation based on the weight of the preference option.

18. The system as claimed in claim 16 wherein the control unit is configured to identify a variety preference.

19. The system as claimed in claim 16 wherein the control unit is configured to identify a user'"'"'s demographic.

20. The system as claimed in claim 16 wherein the control unit is configured to:

identify a discount preference associated with the group behavior; and

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