Abstract
Geo-referencing is a key task for geographical information retrieval because it allows unstructured or textual documents (i.e., Web pages) to be associated with geographical locations, which are then used by geo-search engines to index documents and search information by spatial criteria. This work proposes a strategy to extract geo-references from textual documents that combine natural language-processing techniques and co-reference solving heuristics, which in turn can be used to expand a geographical gazetteer. Implicit geographical entities (i.e., those entities referred to by pronouns) are recognized and incorporated into the gazetteer that is updated and used for geo-referencing tasks. Experiments show the promise of the approach to geo-referencing Web pages when dealing with implicit and/or indirect geo-references.
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