1 引言 关键词：并行聚类；计算机集群；数据库；延展性 [gap=812]Key words】parallel clustering; computer colony; database; extensibility
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并行划分聚类 parallel partitional clustering algorithm
Secondly, this paper studied the parallel algorithm model, and designed a parallel clustering algorithm based on the density, it can make the parallel clustering time complexity into O(n/P) through three time computing with the time complexity of O(n~2/P) .
通过对并行计算模型的研究,设计了一种基于密度的并行聚类算法,通过3次时间复杂度为O(n~2/P)的并行运算,能使并行聚类过程的时间复杂度变为O(n/P)。
参考来源 - 基于密度的并行聚类算法研究·2,447,543篇论文数据，部分数据来源于NoteExpress
文章通过理论分析，认为可以根据并行聚类算法的时间特性来决定采用何种通信策略。
This paper analyzes theoretically that the communication scheme can be chosen according to the time-character of clustering algorithm.
起源于并行学习算法对数据划分的要求，在对一种现行等分割聚类算法进行改进的基础上，本文提出自己的等分聚类算法。
Rooted in the requirement of data partitioning in parallel learning, we proposed our cluster method by improving a current clustering equally method.
〉基因表达数据的并行双向聚类算法。
A systematic comparison and evaluation of biclustering methods for gene expression data.
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