Navigation system with point of interest classification mechanism and method of operation thereof
First Claim
1. A method of operation of a navigation system comprising:
- generating a training data with a control unit from a randomly sampled uncategorized point of interest;
generating a trained classifier model by training a classifier model using the training data;
generating a category identifier and confidence score for an uncategorized point of interest using the trained classifier model;
generating a categorized point of interest by assigning the category identifier to the uncategorized point of interest;
calculating a weighted confidence score based on a weighted F-measure for the category identifier, a pair of the category identifier and the confidence score;
consolidating the categorized point of interest based on the weighted confidence score for the category identifier being meeting or exceeding a threshold for displaying on a device;
searching a total category set for the categorized point of interest;
generating a minimum category set contains an incorrect category identifier from the total category set; and
generating a maximum category set without the incorrect category identifier by eliminating the minimum category set from the total category set for the categorized point of interest.
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Abstract
A method of operation of a navigation system includes: generating a training data from a randomly sampled uncategorized point of interest; generating a trained classifier model by training a classifier model using the training data; generating a category identifier, a confidence score, or a combination thereof for an uncategorized point of interest using the trained classifier model; generating a categorized point of interest by assigning the category identifier to the uncategorized point of interest; calculating a weighted confidence score based on a weighted F-measure for the category identifier, a pair of the category identifier and the confidence score; and consolidating the categorized point of interest based on the weighted confidence score for the category identifier being meeting or exceeding a threshold for displaying on a device.
19 Citations
18 Claims
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1. A method of operation of a navigation system comprising:
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generating a training data with a control unit from a randomly sampled uncategorized point of interest; generating a trained classifier model by training a classifier model using the training data; generating a category identifier and confidence score for an uncategorized point of interest using the trained classifier model; generating a categorized point of interest by assigning the category identifier to the uncategorized point of interest; calculating a weighted confidence score based on a weighted F-measure for the category identifier, a pair of the category identifier and the confidence score; consolidating the categorized point of interest based on the weighted confidence score for the category identifier being meeting or exceeding a threshold for displaying on a device; searching a total category set for the categorized point of interest; generating a minimum category set contains an incorrect category identifier from the total category set; and generating a maximum category set without the incorrect category identifier by eliminating the minimum category set from the total category set for the categorized point of interest. - View Dependent Claims (2, 3, 4, 5)
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6. A method of operation of a navigation system comprising:
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generating a training data with a control unit from a randomly sampled uncategorized point of interest; generating a trained classifier model by training a classifier model using the training data; generating a category identifier and a confidence score for an uncategorized point of interest using the trained classifier model; generating a categorized point of interest by assigning the category identifier to the uncategorized point of interest; calculating a weighted confidence score based on a weighted F-measure for the category identifier, a pair of the category identifier and the confidence score; consolidating the categorized point of interest based on the weighted confidence score for the category identifier being meeting or exceeding a threshold for displaying on a device; searching a total category set for the categorized point of interest; generating a minimum category set contains an incorrect category identifier from the total category set; generating a maximum category set without the incorrect category identifier by eliminating the minimum category set from the total category set for the categorized point of interest; and processing mutually exclusive category identifiers for the categorized point of interest by eliminating the incorrect category identifier. - View Dependent Claims (7, 8, 9)
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10. A navigation system comprising:
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a control it for; generating a training data from a randomly sampled uncategorized point of interest, generating a trained classifier model by training a classifier model using the training data, generating a category identifier and a confidence score for an uncategorized point of interest and generating a categorized point of interest with the trained classifier model, calculating a weighted confidence score based on a weighted F-measure for the category identifier, a pair of the category identifier and the confidence score, consolidating the categorized point of interest based on the weighted confidence score for the category identifier being meeting or exceeding a threshold, searching a total category set for the categorized point of interest, generating a minimum category set contains an incorrect category identifier from the total category set, generating a maximum category set without the incorrect category identifier by eliminating the minimum category set from the total category set for the categorized point of interest, and a communication interface, coupled to the control unit, for transmitting the categorized point of interest for displaying on a device. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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Specification