Title
Semantic unlink prediction in evolving social networks through probabilistic description logic
Date Issued
12 December 2014
Access level
metadata only access
Resource Type
conference paper
Author(s)
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
Recently, prediction of new links between two individuals in social networks has gained a lot of attention. However, to fully understand and predict how the network evolves through time, ending relationships also need to be predicted. Although most approaches use graph-based methods for link prediction, these may not be suited for the unlink prediction task. In this paper, we propose an approach for unlink prediction that uses information about the domain of discourse through a probabilistic ontology, specified in the probabilistic description logic CRALC. We empirically evaluated our approach comparing it with standard graph-based and some state of the art unlink methods. The results shows significant improvement on detecting unlinks when considering our proposal.
Start page
372
End page
377
Language
English
OCDE Knowledge area
Ciencias de la información Ciencias de la computación
Scopus EID
2-s2.0-84922550295
Resource of which it is part
Proceedings - 2014 Brazilian Conference on Intelligent Systems, BRACIS 2014
ISBN of the container
9781479956180
Conference
Proceedings - 2014 Brazilian Conference on Intelligent Systems, BRACIS 2014
Sources of information: Directorio de Producción Científica Scopus