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Semi-supervised learning of geographical gazetteers from the internet

Published 1 January 2003Open access
Olga Uryupina
Citations37
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TL;DR

The bootstrapping approach, investigated in this study, allows us to create new gazetteers using only a small seed dataset (1260 words) and the system produces classifiers, which can be used online to determine a class of any geographical name.

Abstract

In this paper we present an approach to the acquisition 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 produces 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%.

Keywords

Computer Science