Advances in Intelligent Data Analysis IX: 9th International by Paul R. Cohen, Niall M. Adams, Michael R. Berthold

By Paul R. Cohen, Niall M. Adams, Michael R. Berthold

This ebook constitutes the refereed court cases of the ninth foreign convention on clever information research, IDA 2010, held in Tucson, AZ, united states in may possibly 2010. The 21 revised papers offered including 2 invited papers have been rigorously reviewed and chosen from greater than forty submissions. All present elements of clever facts research are addressed, rather clever help for modeling and examining complicated, dynamical platforms. issues coated are end-to-end software program structures; modeling complicated platforms corresponding to gene regulatory networks, fiscal structures, ecological platforms, assets comparable to water, and dynamical social platforms comparable to on-line groups; and robustness, scaling homes and different usability matters.

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Additional info for Advances in Intelligent Data Analysis IX: 9th International Symposium, IDA 2010, Tucson, AZ, USA, May 19-21, 2010, Proceedings (Lecture Notes in Computer Science)

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Correlation dimension is particularly useful when one is working with chaotic systems because the attractors of such systems are generally fractal (self-similar). The Lyapunov exponent is a measurement of the average rate at which neighboring state-space points separate. This represents the fundamental notion of chaos: any two points (initial conditions) that are arbitrarily close in state space can diverge from each other exponentially. These definitions and conditions place important requirements on data and algorithms for computing topological invariants.

Alexander et al. stationary phase. Another common situation in the dynamics of real programs is two or more alternating phases. To evaluate how well our methodology works in that situation, we created a program trace that alternates between the row-major microkernel of Section 3 and a column-major version of the same loop. An example time series from one of these experiments is shown in Figure 3(b). Because of the different ways in which these microkernels touch memory, the time series has two clear regimes: the cache miss rate is high when initializing the array in columnmajor order and low in row-major order.

For each verb or noun, Xi , the set maximalConstrainedPatterns is thus divided into several subsets S(Xi ) (Step 6)2 . A subset S(Xi ) is the set of all sequential patterns of maximalConstrainedPatterns containing the item Xi . More formally, S(Xi ) = {S ∈ maximalConstrainedPatterns | Xi S}. Note that Xi are elements labeled as a verb or a noun. The most k (k > 1) representative elements for each S(Xi ) are then computed. Each subset S(Xi ) is then recursively3 mined with a |S(Xi )| support threshold, min supR , equal to max{ , 2} in order to extract frek quent sequential patterns satisfying CG (Steps 7–14).

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