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Titlebook: Data Security and Security Data; 27th British Nationa Lachlan M. MacKinnon Conference proceedings 2012 Springer-Verlag GmbH Berlin Heidelbe

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Joshua R. Porter,Eric Batchelorhis model. This FP-growth-like approach utilizes the prior knowledge provided by the user at the time of input and discovers frequent patterns with a single scan on the transactional dataset. Experimental results on both synthetic and real-world datasets show that the proposed approach is efficient.
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Feedback Loops in Biological Networks Further, the few proposals about them are mainly focused on the vector data model. In this paper, we define spatial and spatio-temporal granularities for raster data models. In our framework, relations and operations between spatial and spatio-temporal granularities are also defined.
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Computational Methods in Synthetic Biologytics for dropping tuples would increase the accuracy of the results and at the same time maintain QoS. In this paper, we introduce load shedding schemes that are based on the application semantics. The techniques presented in this paper complement existing load shedding approaches.
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An Efficient Approach to Mine Rare Association Rules Using Maximum Items’ Support Constraintshis model. This FP-growth-like approach utilizes the prior knowledge provided by the user at the time of input and discovers frequent patterns with a single scan on the transactional dataset. Experimental results on both synthetic and real-world datasets show that the proposed approach is efficient.
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Defining Spatio-Temporal Granularities for Raster Data Further, the few proposals about them are mainly focused on the vector data model. In this paper, we define spatial and spatio-temporal granularities for raster data models. In our framework, relations and operations between spatial and spatio-temporal granularities are also defined.
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