Faster estimation of the correlation fractal dimension using box-counting

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dc.creatorAttikos, Christos
dc.creatorDoumpos, Michael
dc.date2009-05-26
dc.date.accessioned2026-07-07T13:18:11Z
dc.date.available2026-07-07T13:18:11Z
dc.descriptionFractal dimension is widely adopted in spatial databases and data mining, among others as a measure of dataset skewness. State-of-the-art algorithms for estimating the fractal dimension exhibit linear runtime complexity whether based on box-counting or approximation schemes. In this paper, we revisit a correlation fractal dimension estimation algorithm that redundantly rescans the dataset and, extending that work, we propose another linear, yet faster and as accurate method, which completes in a single pass.
dc.description4 pages, to appear in BCI 2009 - 4th Balkan Conference in Informatics
dc.identifierhttps://arxiv.org/abs/0905.4138
dc.identifierhttp://arxiv.org/abs/0905.4138
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/231351
dc.subjectDatabases
dc.subjectData Structures and Algorithms
dc.titleFaster estimation of the correlation fractal dimension using box-counting
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