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Titlebook: Big Data – BigData 2018; 7th International Co Francis Y. L. Chin,C. L. Philip Chen,Liang-Jie Zha Conference proceedings 2018 Springer Inter

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31#
發(fā)表于 2025-3-26 21:07:26 | 只看該作者
32#
發(fā)表于 2025-3-27 04:46:17 | 只看該作者
Biological Effects of Ion Implantation,p cluster that can effectively replicate and provide an environment for developers to easily design and implement the Spark and Hadoop Map/Reduce programming. Before running their Big Data and deep learning applications in physical multi-node Spark and Hadoop Cluster, developers can conduct Map/Redu
33#
發(fā)表于 2025-3-27 06:33:48 | 只看該作者
34#
發(fā)表于 2025-3-27 11:30:53 | 只看該作者
https://doi.org/10.1007/b135662n petabytes of data. Thus, new technologies and approaches are needed that can efficiently perform complex and time-consuming data analytics without having to rely on expensive super machines..This paper discusses how a distributed machine learning system can be created to efficiently perform Big Da
35#
發(fā)表于 2025-3-27 16:15:59 | 只看該作者
36#
發(fā)表于 2025-3-27 21:47:24 | 只看該作者
Inter-Category Distribution Enhanced Feature Extraction for Efficient Text Classificationthe quality of feature extraction over the text corpus. For supervised learning over text documents, the TF-IDF (Term Frequency-Inverse Document Frequency) weighting factor is one of the most frequently used features in text classification. In this paper, we address two known limitations of TF-IDF b
37#
發(fā)表于 2025-3-28 00:25:36 | 只看該作者
Reversible Data Perturbation Techniques for Multi-level Privacy-Preserving Data Publicationprivacy through data perturbation provide a safe release of datasets such that sensitive information present in the dataset cannot be inferred from the published data. Existing privacy-preserving data publishing solutions have focused on publishing a single snapshot of the data with the assumption t
38#
發(fā)表于 2025-3-28 03:12:36 | 只看該作者
39#
發(fā)表于 2025-3-28 07:02:18 | 只看該作者
40#
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