GIPSY: automated geographic indexing of text documents
Journal of the American Society for Information Science - Special issue: spatial information
A method of geographical name extraction from Japanese text for thematic geographical search
Proceedings of the eighth international conference on Information and knowledge management
Disambiguating Geographic Names in a Historical Digital Library
ECDL '01 Proceedings of the 5th European Conference on Research and Advanced Technology for Digital Libraries
Web-a-where: geotagging web content
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Location normalization for information extraction
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
HLT '91 Proceedings of the workshop on Speech and Natural Language
A Graph-Ranking Algorithm for Geo-Referencing Documents
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Introduction to the CoNLL-2003 shared task: language-independent named entity recognition
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Geographic information retrieval in a mobile environment: evaluating the needs of mobile individuals
Journal of Information Science
Extracting focused locations for web pages
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
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Many Web pages are clearly related to specific locations. Identifying this geographic focus is the cornerstone of the next generation of geographic context aware search services. This paper shows a multistage method for assigning a geographic focus to Web pages (GeoReferencing), using several heuristics for toponym disambiguation and a scoring function for focus determination. We provide an experimental methodology for evaluating the accuracy of the system with Web pages in English and Spanish. Finally, we have obtained promising results, reaching an accuracy of over 70% with a town-level resolution.