PubMed is a popular biomedical bibliographic database curated by the US National Library of Medicine. Limitations may be encountered when querying PubMed for studies from or about a particular geographic location. For example, if a citation record does not include the word `Canada' but instead includes `Ontario' as the named place in its text, a PubMed query to find all studies conducted in Canada using only the keyword `Canada' will not be able to retrieve that particular record. We propose that a GeoNames-powered PubMed search has the potential of solving such issues. By bringing in the “intelligence” of a geographic ontology and the ability to reason with place names (e.g., recognise `Ontario' as a province of `Canada'), a search engine can infer implicit meanings in the queried records that are not directly mentioned as free text or as keyword terms in either the citation records or their metadata.
|Number of pages||3|
|Publication status||Published - Jul 2012|
|Event||IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium - Munich, Germany, United Kingdom|
Duration: 22 Jul 2012 → 27 Jul 2012
|Conference||IGARSS 2012 - 2012 IEEE International Geoscience and Remote Sensing Symposium|
|Period||22/07/12 → 27/07/12|