论文标题
从大数据中迈进紧凑的数据
Toward Compact Data from Big Data
论文作者
论文摘要
BigData是一个数据集，其大小超出了处理有价值的原材料的能力，该原材料可以被完善并蒸馏成有价值的特定见解。紧凑型数据是一种优化大型数据集的方法，该数据集可提供最佳资产，而无需处理复杂的BigData。紧凑型数据集包含在细粒度水平上的最大知识模式，以有效和个性化使用BigData的BigData系统。紧凑的数据方法是量身定制的设计，取决于问题情况。本文中各种数据驱动的研究领域已证明了各种紧凑的数据技术。
Bigdata is a dataset of which size is beyond the ability of handling a valuable raw material that can be refined and distilled into valuable specific insights. Compact data is a method that optimizes the big dataset that gives best assets without handling complex bigdata. The compact dataset contains the maximum knowledge patterns at fine grained level for effective and personalized utilization of bigdata systems without bigdata. The compact data method is a tailor-made design which depends on problem situations. Various compact data techniques have been demonstrated into various data-driven research area in the paper.
