Titlebook: Advances in Intelligent Data Analysis IX; 9th International Sy Paul R. Cohen,Niall M. Adams,Michael R. Berthold Conference proceedings 2010

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The Sraffian Contribution: An Evaluation,The IDA Symposium series had evolved into a meeting apparently concerned with routine data mining. This report describes our attempts to re-focus the ninth IDA symposium on objectives derived from the genesis of the series. These attempts included a dramatically modified call for papers, and a drastically changed reviewing procedure.

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Classical and Marxian Political Economy. As the amount of available data increases, so has our interest in analyzing these networks in order to uncover (1) general laws that govern their structure and evolution, and (2) patterns and predictive models to develop better policies and practices. However, a fundamental challenge in dealing wi

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Classical and Modern Branching Processessic constraints (memory, information processing) and features (optimization and evolutionary history) that serve to significantly narrow search spaces and candidate parameter values. We suggest that the property of “adaptive self-awareness”, when applicable, further constrains model selection, such

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Interval Type-2 Fuzzy Logic Controllers,een used successfully in prior work [1,9]. In this paper, we analyze the theoretical underpinnings of this new methodology as it applies to our understanding of computer performance. By doing so, we demonstrate that using nonlinear time series analysis techniques on computer performance data is soun

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Practical Nonlinear Control Systems, mining approach based on recursive sequence mining. The contribution of this work is twofold. First, we present a method based on a cross-fertilization of sequence mining under constraints and recursive pattern mining to produce a user-manageable set of linguistic information extraction rules. More

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https://doi.org/10.1007/978-3-031-32959-3chnologies, such as Twitter. In contrast, depending on the size and location of the earthquake, scientific alerts can take between two to twenty minutes to publish. We describe TED (Twitter Earthquake Detector) a system that adopts social network technologies to augment earthquake response products

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Inversion and Reflecting Brownian Motion,rs are available when building the model. First, labeled training data is used to build a powerful opaque model, called an .. Second, the oracle is applied to production instances, generating predicted target values, which are used as labels. Finally, these newly labeled instances are utilized, in d