Semi-supervised learning of geographical gazetteers from the internet

In this paper we present an approach to the ac-quisition of geographical gazetteers. Instead of creating these resources manually, we propose to extract gazetteers from the World Wide Web, using Data Mining techniques. The bootstrapping approach, investigated in our study, allows us to create new gazetteers using only a small seed dataset (1260 words). In addition to gazetteers, the system pro-duces classifiers. They can be used online to determine a class (CITY, ISLAND, RIVER, MOUNTAIN, REGION, COUNTRY) of any geographical name. Our classifiers perform with the average accuracy of 86.5%.