Para acceder a los documentos con el texto completo, por favor, siga el siguiente enlace: http://hdl.handle.net/2117/12503

KnowNet: building a large net of knowledge from the web
Cuadros Oller, Montserrat; Rigau Claramunt, German
Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics; Universitat Politècnica de Catalunya. GPLN - Grup de Processament del Llenguatge Natural
This paper presents a new fully automatic method for building highly dense and accurate knowledge bases from existing semantic resources. Basically, the method uses a wide-coverage and accurate knowledge-based Word Sense Disambiguation algorithm to assign the most appropriate senses to large sets of topically related words acquired from the web. KnowNet, the resulting knowledge-base which connects large sets of semantically related concepts is a major step towards the autonomous acquisition of knowledge from raw corpora. In fact, KnowNet is several times larger than any available knowledge resource encoding relations between synsets, and the knowledge KnowNet contains outperform any other resource when is empirically evaluated in a common framework.
Peer Reviewed
Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Llenguatge natural
Natural language processing (Computer science) -- Research
KnowNet
Llenguatge natural (Informàtica) -- Processament
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
info:eu-repo/semantics/submittedVersion
info:eu-repo/semantics/conferenceObject
         

Mostrar el registro completo del ítem

Documentos relacionados

Otros documentos del mismo autor/a

Cuadros Oller, Montserrat; Rigau Claramunt, German
Cuadros Oller, Montserrat; Rigau Claramunt, German; Castillo Valdés, Mauro
Cuadros Oller, Montserrat; Rigau Claramunt, German