Abstract
Consistency measures provide an indication on how much a dataset satisfies a set of integrity constraints, which is useful for comparing, integrating and cleaning datasets. This work presents the notion of consistency measures and provides an evaluation of the cognitive adequacy of these measures. It evaluates the impact on the consistency measures of different parameters (overlapping size, external distance, internal distance, crossing length, and touching length) and the relative size of geometries involved in a conflict. While a human-subject testing supports our hypotheses with respect to the parameters, it rejects the significance of the relative size of geometries as a component of the consistency measures.
This work was partially funded by Fondecyt 1080138, Conicyt-Chile and by “Ministerio de Ciencia e Innovación” (PGE and FEDER) refs. TIN2009-14560-C03-02, TIN2010-21246-C02-01 and by “Xunta de Galicia (Fondos FEDER)”, ref. 2010/17.
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Brisaboa, N.R., Luaces, M.R., Rodríguez, M.A. (2011). Cognitive Adequacy of Topological Consistency Measures. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds) Advances in Conceptual Modeling. Recent Developments and New Directions. ER 2011. Lecture Notes in Computer Science, vol 6999. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24574-9_31
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DOI: https://doi.org/10.1007/978-3-642-24574-9_31
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