Topic modeling for entity linking using keyphrase

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dc.contributor	Universitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.contributor	Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural
dc.contributor.author	Mehdizadeh Naderi, Ali
dc.contributor.author	Rodríguez Hontoria, Horacio
dc.contributor.author	Turmo Borras, Jorge
dc.date	2014
dc.identifier.citation	Mehdizadeh, A.; Rodriguez, H.; Turmo, J. Topic modeling for entity linking using keyphrase. A: International Workshop on Natural Language Processing and Cognitive Science. "Proceedings of the 11th International Workshop on Natural Language Processing and Cognitive Science". Venecia: 2014, p. 1-12.
dc.identifier.uri	http://hdl.handle.net/2117/26183
dc.language.iso	eng
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural
dc.subject	Natural language processing (Computer science)
dc.subject	Wikipedia
dc.subject	Tractament del llenguatge natural (Informàtica)
dc.title	Topic modeling for entity linking using keyphrase
dc.type	info:eu-repo/semantics/submittedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	This paper proposes an Entity Linking system that applies a topic modeling ranking. We apply a novel approach in order to provide new relevant elements to the model. These elements are keyphrases related to the queries and gathered from a huge Wikipedia-based knowledge resource
dc.description.abstract	Peer Reviewed