Towards a Benchmark for LOD-Enhanced Knowledge Discovery from Structured Data

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Provided by: RWTH Aachen University
Topic: Data Management
Format: PDF
To leverage on KDD (Knowledge Discovery in Database) architectures designed for business databases, original unbounded RDF (Resource Description Framework) data has to be transformed. The authors report on a use case consisting in adaptation of linked data, around a nucleus of public procurement data, for a data mining challenge event. The generic problems addressed are: linked data sampling; (generalized) concise bounded description extraction; propositionalisation to CSVs (Comma-Separated Values) using SPARQL SELECT; and aggregation behavior assigned by checking conformance to eligibility criteria formulated as SPARQL queries.
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