论文标题
大数据设置中的三个群集
Triclustering in Big Data Setting
论文作者
论文摘要
在本文中，我们描述了针对具有MAPREDUCE模型或现代编程语言提供的平行化机制在分布式环境中进行有效计算的三次算法的版本。三簇算法的OAC家庭由于对三联式正式环境的三元组的独立处理而显示出良好的并行能力。我们提供算法的时间和空间复杂性，并证明其相关性。我们还比较了使用分布式系统和可伸缩性的性能增益。
In this paper, we describe versions of triclustering algorithms adapted for efficient calculations in distributed environments with MapReduce model or parallelisation mechanism provided by modern programming languages. OAC-family of triclustering algorithms shows good parallelisation capabilities due to the independent processing of triples of a triadic formal context. We provide the time and space complexity of the algorithms and justify their relevance. We also compare performance gain from using a distributed system and scalability.
