In this paper we propose a web document classification approach based on an extended version of Probabilistic Relational Models (PRMs). In particular PRMs have been augmented in order to include uncertainty over relationships, represented by hyperlinks. Our extension, called PRM with Relational Uncertainty, has been evaluated on real data for web document classification purposes. Experimental results shown the potentiality of the proposed model of capturing the real semantic relevance of hyperlinks and the capacity of embedding this information in the classification process. © 2010 Springer-Verlag Berlin Heidelberg.
Fersini, E., Messina, V., Archetti, F. (2010). Web Page Classification: A Probabilistic Model with Relational Uncertainty. In International Conference on Information Processing and Management of Uncertainty (pp.109-118). Springer [10.1007/978-3-642-14049-5_12].
Web Page Classification: A Probabilistic Model with Relational Uncertainty
FERSINI, ELISABETTA;MESSINA, VINCENZINA;ARCHETTI, FRANCESCO ANTONIO
2010
Abstract
In this paper we propose a web document classification approach based on an extended version of Probabilistic Relational Models (PRMs). In particular PRMs have been augmented in order to include uncertainty over relationships, represented by hyperlinks. Our extension, called PRM with Relational Uncertainty, has been evaluated on real data for web document classification purposes. Experimental results shown the potentiality of the proposed model of capturing the real semantic relevance of hyperlinks and the capacity of embedding this information in the classification process. © 2010 Springer-Verlag Berlin Heidelberg.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
