Actas de congresos
A scalable probabilistic description logic approach for semantic link prediction
Fecha
2012-05-20Autor
Luna, José Eduardo Ochoa
Revoredo, Kate Cerqueira
Cozman, Fabio Gagliardi
Institución
Resumen
Predicting potential links between unconnected nodes in a network,
as collaboration networks, is a problem of great practical interest. Link prediction
is mostly based on graph-based features and recently, on approaches that
consider semantics of the domain. However, there is uncertainty in these predictions
and considering it, can improve the prediction results. In this paper,
we propose an algorithm for link prediction that uses a probabilistic ontology
described with the probabilistic description logic CRALC. Moreover, our approach
is scalable through a combination with graph-based features. A dataset
based on the Lattes curriculum platform is used to evaluate empirically our
proposal.