Abstract
The task of processing large sets of data which are stored in distributed sources is still a big problem. The determination of a one, consistent version of data could be very time- and cost-consuming. Therefore, the balance between the time of execution and the quality of the integration results is needed. This paper is devoted to a multi-level approach to data integration using the Consensus Theory. The experimental verification of multi-level integration methods has proved that the division of integration task into smaller subproblems gives similar results as the one-level approach, but improves a time performance.
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This article is based upon work from COST Action KEYSTONE IC1302, supported by COST (European Cooperation in Science and Technology).
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Kozierkiewicz-Hetmańska, A., Sitarczyk, M. (2017). The Efficiency Analysis of the Multi-level Consensus Determination Method. In: Nguyen, N., Papadopoulos, G., Jędrzejowicz, P., Trawiński, B., Vossen, G. (eds) Computational Collective Intelligence. ICCCI 2017. Lecture Notes in Computer Science(), vol 10448. Springer, Cham. https://doi.org/10.1007/978-3-319-67074-4_11
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