10. A navigation system comprising: 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.
12. The system as claimed in claim 10 wherein the control unit is for calculating the weighted F-measure for the category identifier based on a weighted precision, a weighted recall and a search weight.