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Titlebook: New Frontiers in Mining Complex Patterns; First International Annalisa Appice,Michelangelo Ceci,Zbigniew W. Ras Conference proceedings 201

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Francesco Buccafurri,Gianluca Lax,Antonino Nocera,Domenico Ursinomeasures for graphs; metrical properties of graphs; partitions and decompositions; and quantitative graph measures...Structural Analysis of Complex Networks. is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics
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Claire Q,Ross D. Kingmeasures for graphs; metrical properties of graphs; partitions and decompositions; and quantitative graph measures...Structural Analysis of Complex Networks. is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics
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damping and mass terms of the cross-section. In the fourth subsection, building upon the damping mechanics, an extended beam finite element is developed capable of providing the stiffness and damping matrices of the structure, which contain new material coupling terms, essential for describing the
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Learning in the Presence of Large Fluctuations: A Study of Aggregation and Correlationding on the stability exponent of the Lévy distribution. Our results indicate that the correlation in between two attributes may be underestimated if a Gaussian distribution is erroneously assumed. Secondly, we show that, in the scenario where we aim to learn a set of rules to estimate the level of
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Retracted: Machine Learning as an Objective Approach to Understanding Musicctions: a land and sea mask, and a population distribution overlay. The best-performing prediction method achieved a median land distance error of 1,506km, with comparable random trials having mean of medians 3,190km - this is significant at P < 0.001.
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Pair-Based Object-Driven Action Rulesor temporal and object-driven systems. The focus of this paper will be on our proposed pair-based approach, along with the modifications required to extract action rules and calculate their properties.
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Effectively Grouping Trajectory Streamsting from data preparation task that allows us to make the mining step quite effective. Since the validation of data mining approaches has to be experimental we performed several tests on real world datasets that confirmed the efficiency and effectiveness of the proposed technique.
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Improving Robustness and Flexibility of Concept Taxonomy Learning from Texterent kinds of relationships among concepts, where each arc/relationship is associated to a weight that represents its likelihood among all ., and to face the problem of sparse knowledge by using generalizations among distant concepts as bridges between disjoint portions of knowledge.
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