Mining a Multilingual Geographical Gazetteer from the Web

Geographical gazetteers are necessary in a wide variety of applications. In the past, the construction of such gazetteers has been a tedious, manual process and only recently have the first attempts to automate the gazetteers creation been made. Here we describe our approach for mining accurate but large-scale multilingual geographic information by successively filtering information found in heterogeneous data sources (Flickr, Wikipedia, Panoramio, Web pages indexed by search engines). Statistically cross-checking information found in each site, we are able to identify new geographic objects, and to indicate, for each one, its name, its GPS coordinates, its encompassing regions (city, region, country), the language of the name, its popularity, and the type of the object (church, bridge, etc.). We evaluate our approach by comparing, wherever possible, our multilingual gazetteer to other known attempts at automatically building a geographic database and to Geonames, a manually built gazetteer.