1. A method, comprising: receiving a keyword string of one or more keywords, the keyword string being representative of a geographically-relevant object available on the Web, wherein the geographically-relevant object is an object selected from a group of objects, the group of objects comprising map objects, image objects, and sensor objects; searching geographical data, available on the Web, to identify locations associated with the keyword string; determining a probable location based on the identified locations; associating geographic-related semantic information descriptors of the probable location with the geographically-relevant object by assigning a metadata tag derived from the keyword string to the geographically-relevant object, wherein the metadata tag associates the descriptors with the geographically-relevant object and wherein the associating comprises determining a probable location as a clustering function of the multiple locations; correlating the geographic-related semantic information of the probable location with the geographically-relevant object, wherein the cluster function for computing the probable location from the multiple locations comprises: computing an initial center point as a statistical function that minimizes a sum of the square distances from the initial center point to each one of the multiple locations; removing spurious locations located greater than a predefined distance from a mean of the multiple locations; and computing the probable location for remaining ones of the multiple locations by minimizing a sum of the square distances from the probable location to each one of the remaining ones of the multiple locations; and storing the geographically-relevant object and the metadata tag to allow a web search engine to locate the geographically-relevant object and the metadata tag responsive to a query.