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Titlebook: Data Mining in Large Sets of Complex Data; Robson L. F. Cordeiro,Christos Faloutsos,Caetano T Book 2013 The Author(s) 2013 Analysis of Bre

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發(fā)表于 2025-3-25 05:28:57 | 只看該作者
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發(fā)表于 2025-3-25 10:24:38 | 只看該作者
2191-5768 osis, region detection in satellite images, assistance to clThe amount and the complexity of the data gathered by current enterprises are increasing at an exponential rate. Consequently, the analysis of Big Data is nowadays a central challenge in Computer Science, especially for complex data. For ex
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發(fā)表于 2025-3-25 14:25:33 | 只看該作者
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發(fā)表于 2025-3-25 16:17:22 | 只看該作者
Book 2013a is nowadays a central challenge in Computer Science, especially for complex data. For example, given a satellite image database containing tens of Terabytes, how can we find regions aiming at identifying native rainforests, deforestation or reforestation? Can it be made automatically? Based on the
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發(fā)表于 2025-3-26 06:11:26 | 只看該作者
2191-5768 k considers both: it enables mining complex data from high impact applications, such as breast cancer diagnosis, region classification in satellite images, assistance to climate change forecast, recommendation 978-1-4471-4889-0978-1-4471-4890-6Series ISSN 2191-5768 Series E-ISSN 2191-5776
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發(fā)表于 2025-3-26 20:23:29 | 只看該作者
Glandular Fever (Infectious Mononucleosis)ink, re-design and re-implement existing serial algorithms in order to allow for parallel processing. With that in mind, this chapter presents one work that explores parallelism using MapReduce for clustering huge datasets. Specifically, we describe in detail one second algorithm, named . [.], that
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