Exploring the automatic selection of basic level concepts

Please use this identifier to cite or link to this item: http://hdl.handle.net/10045/2522
Información del item - Informació de l'item - Item information
Title: Exploring the automatic selection of basic level concepts
Authors: Izquierdo Beviá, Rubén | Suárez Cueto, Armando | Rigau Claramunt, German
Research Group/s: Procesamiento del Lenguaje Natural y Sistemas de Información | IXA NLP Group
Center, Department or Service: Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos | Universidad del País Vasco. Departamento de Lenguajes y Sistemas Informáticos
Keywords: WordNet | Word-senses | Levels of abstraction | Word sense disambiguation
Knowledge Area: Procesamiento del Lenguaje Natural
Date Created: Sep-2007
Issue Date: Sep-2007
Publisher: INCOMA
Citation: IZQUIERDO BEVIÁ, Rubén; SUÁREZ CUETO, Armando; RIGAU CLARAMUNT, German. "Exploring the automatic selection of basic level concepts". En: International Conference : Recent Advances in Natural Language Processing : Proceedings / Galia Angelova [et al.] (eds.). Shoumen, Bulgaria : INCOMA, 2007. ISBN 978-954-91743-7-3, pp. 298-302
Abstract: We present a very simple method for selecting Base Level Concepts using basic structural properties of WordNet. We also empirically demonstrate that these automatically derived set of Base Level Concepts group senses into an adequate level of abstraction in order to perform class-based Word Sense Disambiguation. In fact a very naive Most Frequent classifier using the classes selected is able to perform a semantic tagging with accuracy figures over 75%.
Sponsor: Union Europea bajo proyecto QALL-ME (FP6 IST-033860) y el Gobierno Español bajo el proyecto Text-Mess (TIN2006-15265-C06-01) y KNOW (TIN2006-15049-C03-01)
URI: http://hdl.handle.net/10045/2522
ISBN: 978-954-91743-7-3
Language: eng
Type: info:eu-repo/semantics/bookPart
Peer Review: si
Appears in Collections:INV - GPLSI - Capítulos de Libros

Files in This Item:
Files in This Item:
File Description SizeFormat 
Thumbnailranlp07BLC2.pdf180,69 kBAdobe PDFOpen Preview

Items in RUA are protected by copyright, with all rights reserved, unless otherwise indicated.