Merging Closed Pattern Sets in Distributed Multi-Relational Data
Merging Closed Pattern Sets in Distributed Multi-Relational Data
复制标题
DOI：
--
复制
发表时间：
2014
期刊：
影响因子：
--
通讯作者：
H. Seki;Yohei Kamiya
中科院分区：
文献类型：
--
作者：
H. Seki;Yohei Kamiya
研究了分布式环境下多关系数据库中封闭模式的挖掘问题。给定两个局部数据库（水平分区）及其封闭模式（概念）集，利用形式概念分析中的合并（或子置）算子，生成全局数据库中的封闭模式集。由于合并操作的执行时间随着本地数据库数量的增加而增加，因此我们提出了一些改进合并操作的方法。我们还提出了一些实验结果，使用分布式计算环境的基础上MapReduce框架，这表明所提出的方法的有效性。
We consider the problem of mining closed patterns from multi-relational databases in a distributed environment. Given two lo- cal databases (horizontal partitions) and their sets of closed patterns (concepts), we generate the set of closed patterns in the global database by utilizing the merge (or subposition) operator, studied in the field of Formal Concept Analysis. Since the execution times of the merge opera- tions increase with the increase in the number of local databases, we pro- pose some methods for improving the merge operations. We also present some experimental results using a distributed computation environment based on the MapReduce framework, which shows the effectiveness of the proposed methods.