TALP at MediaEval 2011 Placing Task: georeferencing Flickr videos with geographical knowledge and information retrieval

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/17700

dc.contributor	Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
dc.contributor	Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural
dc.contributor.author	Ferrés Domènech, Daniel
dc.contributor.author	Rodríguez Hontoria, Horacio
dc.date	2011
dc.identifier.citation	Ferrés, D.; Rodríguez, H. TALP at MediaEval 2011 Placing Task: georeferencing Flickr videos with geographical knowledge and information retrieval. A: MediaEval Workshop. "Working notes proceedings of the MediaEval 2011 workshop: Santa Croce in Fossabanda, Pisa, Italy, September 1-2, 2011". Pisa: 2011.
dc.identifier.uri	http://hdl.handle.net/2117/17700
dc.language.iso	eng
dc.relation	http://ceur-ws.org/Vol-807/
dc.rights	Attribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural
dc.subject	Information retrieval
dc.subject	Georeferencing
dc.subject	Toponym disambiguation
dc.subject	Geographical knowledge bases
dc.subject	Recuperació de la informació
dc.title	TALP at MediaEval 2011 Placing Task: georeferencing Flickr videos with geographical knowledge and information retrieval
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	This paper describes our Georeferencing approaches, experiments, and results at the MediaEval 2011 Placing Task evaluation. The task consists of predicting the most probable geographical coordinates of Flickr videos. Our approaches used only Flickr users textual annotations and tagsets to predict. We used three approaches for this task: 1) a Geographical Knowledge approach, 2) an Information Retrieval based approach with Re-Ranking, and 3) a combination of both (GeoFusion). The GeoFusion approach achieved the best results within the margin of errors from 10km to 10000km.

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