Towards Learning to Rank in Description Logics

Authors:
Nicola Fanizzi;Claudia d'Amato;Floriana Esposito
Affiliations:
University of Bari, Italy, email: {fanizzi, claudia.damato, esposito}@di.uniba.it;University of Bari, Italy, email: {fanizzi, claudia.damato, esposito}@di.uniba.it;University of Bari, Italy, email: {fanizzi, claudia.damato, esposito}@di.uniba.it
Venue:
Proceedings of the 2010 conference on ECAI 2010: 19th European Conference on Artificial Intelligence
Year:
2010

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Abstract

In the context of knowledge bases expressed in Description Logics, a method for learning functions that can predict the ranking of resources encoding some preference criteria implicitly encoded through examples of rated individuals. The method relies on a kernelized version of the PERCEPTRON RANKING algorithm which is suitable for batch but also online problem settings.