Bounds on the Sample Complexity of Bayesian Learning Using Information Theory and the VC Dimension
Machine Learning - Special issue on computational learning theory
A survey of kernels for structured data
ACM SIGKDD Explorations Newsletter
Kernels and Distances for Structured Data
Machine Learning
The Description Logic Handbook
The Description Logic Handbook
An algorithm based on counterfactuals for concept learning in the Semantic Web
Applied Intelligence
Evolutionary Conceptual Clustering of Semantically Annotated Resources
ICSC '07 Proceedings of the International Conference on Semantic Computing
Inductive concept retrieval and query answering with semantic knowledge bases through kernel methods
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part I
Kernel methods for mining instance data in ontologies
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
A declarative kernel for concept descriptions
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Relational kernel machines for learning from graph-structured RDF data
ESWC'11 Proceedings of the 8th extended semantic web conference on The semantic web: research and applications - Volume Part I
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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 machinethat 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.