Learning Probabilistic Relational Models
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Learning probabilistic models of link structure
The Journal of Machine Learning Research
Fast webpage classification using URL features
Proceedings of the 14th ACM international conference on Information and knowledge management
A comparison of implicit and explicit links for web page classification
Proceedings of the 15th international conference on World Wide Web
Granular modeling of web documents: impact on information retrieval systems
Proceedings of the 10th ACM workshop on Web information and data management
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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.