Type inference through the analysis of wikipedia links

DBpedia contains millions of untyped entities, either if we consider the native DBpedia ontology, or Yago plus Word- Net. Is it possible to automatically classify those entities? Based on previous work on wikilink invariances, we wondered if wikilinks convey a knowledge rich enough for their classification. In this paper we give three contributions. Concerning the DBpedia link structure, we describe some measurements and notice both problems (e.g. the bias that could be induced by the incomplete ontological coverage of the DBpedia ontology), and potentials existing in current type coverage. Concerning classification, we present two techniques that exploit wikilinks, one based on induction from machine learning techniques, and the other on abducfition. Finally, we discuss the limited results of classification, which confrmed our fears expressed in the description of general figures from the measurement. We also suggest some new possible directions to entity classification that could be taken.

Tipo Pubblicazione: 
Contributo in atti di convegno
Author or Creator: 
Nuzzolese, Andrea Giovanni
Gangemi, Aldo
Presutti, Valentina
Ciancarini, Paolo
Publisher: 
M. Jeusfeld c/o Redaktion Sun SITE, Informatik V, RWTH Aachen., Aachen, Germania
Source: 
WWW 2012 Workshop on Linked Data on the Web, LDOW 2012, 2012
Date: 
2012
Resource Identifier: 
http://www.cnr.it/prodotto/i/301589
http://www.scopus.com/inward/record.url?eid=2-s2.0-84893201690&partnerID=q2rCbXpz
Language: 
Eng