Abstract
This work proposes a family of language-independent semantic kernel functions defined for individuals in an ontology. This allows exploiting well-founded kernel methods for several mining applications related to OWL knowledge bases. Namely, our method integrates the novel kernel functions with a support vector machine that can be set up to work with these representations. In particular, we present preliminary experiments where statistical classifiers are induced to perform the tasks of instance classification and retrieval.
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d’Amato, C., Fanizzi, N., Esposito, F. (2008). Classification and Retrieval through Semantic Kernels. In: Lovrek, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2008. Lecture Notes in Computer Science(), vol 5179. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85567-5_32
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DOI: https://doi.org/10.1007/978-3-540-85567-5_32
Publisher Name: Springer, Berlin, Heidelberg
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