A Semantic Web Approach to Pattern Discovery in Data and Music
In Music Information Retrieval (MIR), as in many other research areas currently, there is an increasing push towards publishing metadata using the Resource Description Framework (RDF), as well as creating and re-using ontologies to make explicit the meaning of that data. Inevitably though, this metadata is created and/or interpreted using some form of signal processing or algorithmic computation, typically performed using technologies that sit outside of the Semantic Web domain. This usual approach ignores the fact that computations may be performed by the SPARQL query language, and that the web ontology language (OWL) offers the power of logical inferencing. In this paper we show that it is possible to implement a complete pattern discovery algorithm (the SIATEC algorithm), using purely the SPARQL query language, acting on RDF data in tandem with a small OWL ontology. We describe the challenges encountered by taking this approach, the particular solution we've arrived at, and we evaluate performance by comparing execution time against a more conventional implementation.
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