Abstract
A domain ontology (DO) is a machine-readable knowledge repository which, whenever properly exploited, can help to discover meaningful and intelligible patterns from compatible datasets. Yet since such data is naturally graph-shaped, the corresponding task amounts to mining what we call ontologically-generalized graph patterns. We study the underlying problem within a dairy production context where a dedicated DO has been designed beforehand. Two alternative mining approaches have been designed, both representing adaptations of methods from the literature. We evaluated them on an excerpt from our dairy production dataset and report here their respective limitations. We also sketch a way to approach the design of ontology-powered graph miner.
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