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Titlebook: Algorithms and Architectures for Parallel Processing; 15th International C Guojun Wang,Albert Zomaya,Kenli Li Conference proceedings 2015 S

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https://doi.org/10.1007/978-3-642-47441-5ig data. Along the way, the critical issue is how to minimize the communication overhead of the distributed sequential pattern mining algorithm and maximize its execution efficiency by balancing the workload of distributed computing resources. To address such an issue, this paper proposes a MapReduc
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https://doi.org/10.1007/978-3-8350-9379-9mation retrieval and data mining field gradually. These studies have achieved some success while still having very great limitations to deal with abundant features of documents. Things get worser especially in the big data environment, where the documents amount is considerably huge. In order to add
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Strategisches Kompetenz-Management of multi-fractal dimensions and singular index of natural images general have large variation range. Based on this, multi-fractal spectrum features of photo response non-uniformity noise (PRNU) are used for the identification of natural images and computer generated graphics. 9 dimensions of textur
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https://doi.org/10.1007/978-3-8350-9379-9e with a global score. There are two shortcomings of this strategy, i.e., partially predominant features submerged and classification redundancies for multi-features estimated inappropriately. In this paper, a new feature selection method based on . and . is proposed. Classification bias describes f
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https://doi.org/10.1007/978-3-8350-9379-9s in the given document collection to the document. By restricting the relatedness to the expected frequencies that each word will occur in the document, the traditional weighted sum of word vectors is proved to give the upper bounds of the expected frequencies. Duplicate counts usually exist during
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Strategisches Kompetenz-Managementfic accident data from October 2014 to March 2015 in Xiamen, China, we propose a novel accident occurrences analytics method in both spatial and temporal dimensions to predict when and where an accident with a specific crash type will occur consequentially by whom. Firstly, we analyze and visualize
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Guojun Wang,Albert Zomaya,Kenli LiIncludes supplementary material:
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