Title :
Faster Estimation of the Correlation Fractal Dimension Using Box-counting
Author :
Attikos, Christos ; Doumpos, Michael
Author_Institution :
Manage. Consulting Div., Accenture S.A., Kifissia, Greece
Abstract :
Fractal 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.
Keywords :
correlation methods; data mining; fractals; visual databases; approximation schemes; box-counting; correlation fractal dimension faster estimation; data mining; dataset skewness; linear runtime complexity; spatial databases; state-of-the-art algorithms; Approximation algorithms; Clustering algorithms; Conference management; Data mining; Electronic mail; Fractals; Informatics; Runtime; Spatial databases; State estimation; Box-counting; Databases; Fractal dimension;
Conference_Titel :
Informatics, 2009. BCI '09. Fourth Balkan Conference in
Conference_Location :
Thessaloniki
Print_ISBN :
978-0-7695-3783-2
