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dc.date.accessioned 2012-11-08T16:45:29Z
dc.date.available 2012-11-08T16:45:29Z
dc.date.issued 2006-08
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23916
dc.description.abstract This paper describes a technique to extract geographic location information from a natural language description of a location. The technique relies on a set of domain specific tags and a set of keywords. The tags are used to identify roads, intersections, and landmarks. Tag combinations are used to discover road segments. The technique is applied to understanding highway construction reports for the Canadian Province of Ontario. en
dc.language en es
dc.subject geographic location information en
dc.subject Ubicaciones Geográficas es
dc.subject tags en
dc.subject Procesamiento de Lenguaje Natural es
dc.subject keywords en
dc.title Road segment identification in natural language text en
dc.type Objeto de conferencia es
sedici.identifier.isbn 0-387-34654-6 es
sedici.creator.person Barsanti, Lawrence es
sedici.creator.person Tawfik, Ahmed Y. es
sedici.description.note IFIP International Conference on Artificial Intelligence in Theory and Practice - Speech and Natural Language es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2006-08
sedici.relation.event 19 th IFIP World Computer Congress - WCC 2006 es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)