On the Geo-Indicativeness of Non-Georeferenced Text (2012)
Type of ContentConference Contributions - Published
Geographic location is a key component for information retrieval on the Web, recommendation systems in mobile computing and social networks, and place-based integration on the Linked Data cloud. Previous work has addressed how to estimate locations by named entity recognition, from images, and via structured data. In this paper, we estimate geographic regions from unstructured, non geo-referenced text by computing a probability distribution over the Earth’s surface. Our methodology combines natural language processing, geostatistics, and a data-driven bottom-up semantics. We illustrate its potential for mapping geographic regions from non geo-referenced text.
CitationAdams BT, Janowicz K (2012). On the Geo-Indicativeness of Non-Georeferenced Text. Dublin, Ireland: ICWSM 2012. 05/06/2012-07/06/2012. Proceedings of the Sixth International AAAI Conference on Weblogs and Social Media. 375-378.
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ANZSRC Fields of Research46 - Information and computing sciences::4606 - Distributed computing and systems software::460608 - Mobile computing
08 - Information and Computing Sciences::0805 - Distributed Computing::080505 - Web Technologies (excl. Web Search)
47 - Language, communication and culture::4704 - Linguistics::470409 - Linguistic structures (incl. phonology, morphology and syntax)
20 - Language, Communication and Culture::2004 - Linguistics::200402 - Computational Linguistics
04 - Earth Sciences::0406 - Physical Geography and Environmental Geoscience
40 - Engineering::4013 - Geomatic engineering::401302 - Geospatial information systems and geospatial data modelling
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Janowicz, Krzysztof; Adams, Ben (2014)
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