Titlebook: Advances in Data Mining: Applications and Theoretical Aspects; 10th Industrial Conf Petra Perner Conference proceedings 2010 Springer-Verla

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Processing Handwritten Words by Intelligent Use of OCR Resultsrnational law and international relations, as well as to-day’s post-BREXIT practitioners, a comprehensive guide to the wide range of legal instruments and negotiating strategies that may be used to govern and regulate a major industry within the framework of a Treaty relationship..978-3-319-88085-3978-3-319-65705-9

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Entropic Quadtrees and Mining Mars Craterse contributors explore the art of performance in Mtukudzi’s music and acting career, and how this facilitated his reconstruction agenda, offering fresh and compelling perspectives into the role of performing artists and cultural workers such as Mtukudzi in presenting models for reconstructing the world..978-3-030-80730-6978-3-030-80728-3

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0302-9743 ics in data mining: Data Mining in Marketing DMM, Data Mining in LifeScience DMLS, the Workshop on Case-Based Reasoning for Multimedia Data CBR-MD, and the Workshop on Data Mining in Agriculture DMA. The Workshop on Data Mining in Agricu978-3-642-14399-1978-3-642-14400-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Front Matterovannini was an influential macroeconomist and financial economist. His vast legacy of studies and ideas prompted this book in his honor, on the occasion of his untimely passing away.. .. .978-3-030-60370-0978-3-030-60368-7

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Describing Data with the Support Vector Shell in Distributed Environmentsurance companies using measures of efficiency and competition. By helping regulatory authorities determine the future course of action in the context of entry of foreign insurers and also in establishing a leve978-981-10-9568-9978-981-10-2233-3

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https://doi.org/10.1057/9781137001382nt a new metric to evaluate the quality of a clustering algorithm to overcome the limitations of existing cluster evaluation techniques. This new metric is based on the path length of the elements of a cluster and avoids judging the quality based on cluster density. We show the effectiveness of the

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