Abstract
This paper introduces a method for analyzing web datasets based on key dependencies. The classical notion of a key in relational databases is adapted to RDF datasets. In order to better deal with web data of variable quality, the definition of a pseudo-key is presented. An RDF vocabulary for representing keys is also provided. An algorithm to discover keys and pseudo-keys is described. Experimental results show that even for a big dataset such as DBpedia, the runtime of the algorithm is still reasonable. Two applications are further discussed: (i) detection of errors in RDF datasets, and (ii) datasets interlinking.
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Atencia, M., David, J., Scharffe, F. (2012). Keys and Pseudo-Keys Detection for Web Datasets Cleansing and Interlinking. In: ten Teije, A., et al. Knowledge Engineering and Knowledge Management. EKAW 2012. Lecture Notes in Computer Science(), vol 7603. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33876-2_14
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DOI: https://doi.org/10.1007/978-3-642-33876-2_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33875-5
Online ISBN: 978-3-642-33876-2
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