Research at Sofia University >
OpenAIRE >
S3T 2009 >

Please use this identifier to cite or link to this item: http://hdl.handle.net/10506/652

Title: Graph-based Semantic Relatedness for Named Entity Disambiguation
Authors: Gentile, Anna Lisa
Zhang, Ziqi
Xia, Lei
Iria, José
Keywords: Named Entity Disambiguation
Graph-based Semantic Relatedness
Issue Date: 2009
Publisher: Demetra EOOD
Citation: Gentile, Anna Lisa, Zhang, Ziqi, Xia, Lei, Iria, José (2009), Graph-based Semantic Relatedness for Named Entity Disambiguation, Proceedings of International Conference on SOFTWARE, SERVICES & SEMANTIC TECHNOLOGIES, October 28-29, 2009, Sofia, Bulgaria, ISBN 978-954-9526-62-2, p. 13
Abstract: Natural Language is a mean to express and discuss about concepts, objects, events, i.e. it carries semantic contents. The SemanticWeb aims at tightly coupling contents with their precise meanings. One of the ultimate roles of Natural Language Processing techniques is identifying the meaning of the text, providing effective ways to make a proper linkage between textual references and real world objects. This work adresses the problem of giving a sense to proper names in a text, that is automatically associating words representing Named Entities with their identities. The proposed methodology for Named Entity Disambiguation is based on Semantic Relatedness Scores obtained with a graph based model overWikipedia.We show that, without building a Bag of Words representation of text, but only considering named entities within the text, the proposed paradigm achieves results competitive with the state of the art on a news story dataset.
URI: http://hdl.handle.net/10506/652
ISBN: 978-954-9526-62-2
Appears in Collections:S3T 2009

Files in This Item:

File Description SizeFormat
S3T2009_06_ALGentile_ZZhang_LXia_JIria.pdf348.01 kBAdobe PDFView/Open
View Statistics

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


Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback