Transductive Inference for Class-Membership Propagation in Web Ontologies

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Abstract

Considering the increasing availability of structured machine processable knowledge in the context of the Semantic Web, only relying on purely deductive inference may be limiting. This work proposes a new method for similarity-based class-membership prediction in Description Logic knowledge bases. The underlying idea is based on the concept of propagating class-membership information among similar individuals; it is non-parametric in nature and characterised by interesting complexity properties, making it a potential candidate for large-scale transductive inference. We also evaluate its effectiveness with respect to other approaches based on inductive inference in SW literature.

Autore Pugliese

Tutti gli autori

  • D'AMATO C.;ESPOSITO F.;FANIZZI N.

Titolo volume/Rivista

Non Disponibile

Anno di pubblicazione

2013

ISSN

0302-9743

ISBN

978-3-642-38287-1

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

4

Ultimo Aggiornamento Citazioni

Non Disponibile

Settori ERC

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Codici ASJC

Non Disponibile