Application-Oriented Succinct Data Structures for Big Data, The Review of Socionetwork Strategies
Application-Oriented Succinct Data Structures for Big Data, The Review of Socionetwork Strategies
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面向应用的大数据简洁数据结构，社会网络策略回顾
DOI：
10.1007/s12626-019-00045-1
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Tetsuo Shibuya
中科院分区：
文献类型：
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作者：
Yoichi Sasaki;Tetsuo Shibuya;Kimihito Ito;and Hiroki Arimura;Tetsuo Shibuya
如果一个数据结构的渐近空间要求与原始数据大小相匹配，则该数据结构被称为简洁的。开发简洁的数据结构是处理爆炸性增长的大数据的重要因素。此外，最近在各个领域中产生了更广泛的大数据变化，并且非常需要开发更具体的应用程序简洁的数据结构。在这项研究中，我们回顾了最近提出的面向应用的简洁的数据结构的大数据应用在三个不同的领域：隐私保护计算密码学，生物信息学中的基因组组装，压缩通信的工作空间减少。
A data structure is called succinct if its asymptotical space requirement matches the original data size. The development of succinct data structures is an important factor to deal with the explosively increasing big data. Moreover, wider variations of big data have been produced in various fields recently and there is a substantial need for the development of more application-specific succinct data structures. In this study, we review the recently proposed application-oriented succinct data structures motivated by big data applications in three different fields: privacy-preserving computation in cryptography, genome assembly in bioinformatics, and work space reduction for compressed communications.