Ranking Entities in a Large Semantic Network

DOI:	https://doi.org/10.1007/978-3-319-11955-7_30
URL:	http://2014.eswc-conferences.org/sites/default/fil...
Additional URL:	http://dws.informatik.uni-mannheim.de/fileadmin/le...
Document Type:	Conference or workshop publication
Year of publication:	2014
Book title:	The Semantic Web: ESWC 2014 Satellite Events : ESWC 2014 Satellite Events, Anissaras, Crete, Greece, May 25-29, 2014, Revised Selected Papers
The title of a journal, publication series:	Lecture Notes in Computer Science
Volume:	8798
Page range:	254-258
Date of the conference:	25.05.2014
Publisher:	Presutti, Valentina
Place of publication:	Berlin [u.a.]
Publishing house:	Springer
ISBN:	978-3-319-11954-0 , 978-3-319-11955-7
ISSN:	0302-9743 , 1611-3349
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Semantic Web (Juniorprofessur) (Ponzetto 2013-2015) School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject:	004 Computer science, internet
Abstract:	We present two knowledge-rich methods for ranking entities in a semantic network. Our approach relies on the DBpedia knowledge base for acquiring fine-grained information about entities and their semantic relations. Experiments on a benchmarking dataset show the viability of our approach.

Dieser Eintrag ist Teil der Universitätsbibliographie.

BASE: Schuhmacher, Michael ; Ponzetto, Simone Paolo

Google Scholar: Schuhmacher, Michael ; Ponzetto, Simone Paolo

ORCID: Schuhmacher, Michael and Ponzetto, Simone Paolo

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