Navigation system with error detection mechanism and method of operation thereof

• US 9,273,972 B2
• Filed: 03/14/2014
• Issued: 03/01/2016
• Est. Priority Date: 03/14/2014
• Status: Active Grant

• Current Assignee: TeleNav Incorporated
• Original Assignee: TeleNav Incorporated
• Inventors: Narasimha, Pramod Lakshmi, Husain, Aliasgar Mumtaz
• Primary Examiner(s): MARC-COLEMAN, MARTHE Y
• Application Number:
  US14/211,239
• Publication Number:
  US 20150260533A1
• Time in Patent Office: 718 Days
• Field of Search: 701/400, 701/532, 707/E17.018, 707/E17.109
• US Class Current: 1/1
• CPC Class Codes: G01C 21/34 Route searching; Route guidance
• CPC Class Codes: G01C 21/3679 Retrieval, searching and output of POI information, e.g. hotels, restaurants, shops, filling stations, parking facilities G01C21/3611 takes precedence
• CPC Class Codes: G06F 16/9537 Spatial or temporal dependent retrieval, e.g. spatiotemporal queries

Abstract

A method of operation of a navigation system includes: accessing points of interest; identifying a target of interest including a field selection based on accessing the points of interest; generating a categorical set and a further set from the points of interest based on the field selection of the target of interest; calculating an error-related probability based on the categorical set and the further set; and determining an erroneous entry associated with the target of interest based on the error-related probability for displaying on a device.

Claims

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

accessing points of interest;

identifying a target of interest including a field selection based on accessing the points of interest;

generating a categorical set and a further set from the points of interest based on the field selection of the target of interest;

calculating an error-related probability based on the categorical set and the further set; and

determining an erroneous entry associated with the target of interest based on the error-related probability for displaying on a device.

2. The method as claimed in claim 1 wherein generating the categorical set and the further set includes generating the categorical set and the categorical set based on a correlative categorical relationship associated with the field selection.

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

generating an intersection set and a union set based on the categorical set and the further set; and

wherein;

calculating the error-related probability includes calculating the error-related probability based on the intersection set and the union set.

4. The method as claimed in claim 1 wherein calculating the error-related probability includes:

calculating an error-absent probability, an error-inclusion probability, a target-error probability, and a target-correct probability; and

calculating a target-overall probability based on the error-absent probability, the error-inclusion probability, the target-error probability, and the target-correct probability.

5. The method as claimed in claim 1 further comprising generating a corrective estimation for replacing the erroneous entry.

6. The method as claimed in claim 1 wherein:

identifying the target of interest includes identifying the target of interest including the field selection and the further selection based on accessing the points of interest; and

generating the categorical set and the further set includes generating the categorical set and the further set from the points of interest based on the field selection and the further selection, the categorical set and the further set each including at least three instances of the points of interest.

7. The method as claimed in claim 6 wherein generating the categorical set and the further set includes generating the categorical set and the further set based on a correlative categorical relationship between the field selection and the further selection with the categorical set corresponding to the field selection and the further set corresponding to the further selection.

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

generating an intersection set including one or more instances of the points of interest occurring in both the categorical set and the further set;

generating a union set based on combining the categorical set and the further set; and

wherein;

calculating the error-related probability includes calculating the error-related probability based on a set count associated with the categorical set, the further set, the intersection set, the union set, or a combination thereof.

9. The method as claimed in claim 6 wherein calculating the error-related probability includes:

calculating an error-absent probability and an error-inclusion probability independent of the target of interest;

calculating a target-error probability and a target-correct probability given the target of interest; and

calculating a target-overall probability according to a calculation mechanism based on the error-absent probability, the error-inclusion probability, the target-error probability, and the target-correct probability.

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

selecting a candidate category value based on the categorical set, the further set, or a combination thereof;

calculating the error-related probability corresponding to the target of interest including the candidate category value instead of the erroneous entry; and

generating a corrective estimation for replacing the erroneous entry.

11. A navigation system comprising:

a storage interface for accessing points of interest;

a control unit, coupled to the storage interface, configured to;

identify a target of interest including a field selection based on accessing the points of interest,

generate a categorical set and a further set from the points of interest based on the field selection of the target of interest,

calculate an error-related probability based on the categorical set and the further set, and

determine an erroneous entry associated with the target of interest based on the error-related probability for displaying on a device.

12. The system as claimed in claim 11 wherein the control unit is configured to generate the categorical set and the categorical set based on a correlative categorical relationship associated with the field selection.

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

generate an intersection set and a union set based on the categorical set and the further set; and

calculate the error-related probability based on the intersection set and the union set.

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

calculate an error-absent probability, an error-inclusion probability, a target-error probability, and a target-correct probability; and

calculate a target-overall probability based on the error-absent probability, the error-inclusion probability, the target-error probability, and the target-correct probability.

15. The system as claimed in claim 11 wherein the control unit is configured to generate a corrective estimation for replacing the erroneous entry.

16. A non-transitory computer readable medium including instructions for a navigation system comprising:

accessing points of interest;

identifying a target of interest including a field selection based on accessing the points of interest;

generating a categorical set and a further set from the points of interest based on the field selection of the target of interest;

calculating an error-related probability based on the categorical set and the further set; and

determining an erroneous entry associated with the target of interest based on the error-related probability for displaying on a device.

17. The non-transitory computer readable medium as claimed in claim 16 wherein generating the categorical set and the further set includes generating the categorical set and the categorical set based on a correlative categorical relationship associated with the field selection.

18. The non-transitory computer readable medium as claimed in claim 16 further comprising:

generating an intersection set and a union set based on the categorical set and the further set; and

wherein;

calculating the error-related probability includes calculating the error-related probability based on the intersection set and the union set.

19. The non-transitory computer readable medium as claimed in claim 16

wherein calculating the error-related probability includes:

calculating an error-absent probability, an error-inclusion probability, a target-error probability, and a target-correct probability; and

calculating a target-overall probability based on the error-absent probability, the error-inclusion probability, the target-error probability, and the target-correct probability.

20. The non-transitory computer readable medium as claimed in claim 16 further comprising generating a corrective estimation for replacing the erroneous entry.