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A parallel algorithm based on search space partition for generating concepts

机译:基于搜索空间划分的并行概念生成算法

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Concept lattice, the core data structure in formal concept analysis, has been used widely in machine learning, data mining and knowledge discovery, information retrieval, etc. The main difficulty with concept lattice-based system comes from the lattice construction itself. In this paper, a parallel algorithm based on the closure search space partition for computing concepts is proposed. This algorithm divides the closure search space into several subspaces in accordance with criterions prescribed ahead and introduces an efficient scheme to recognize the valid ones, in which the searching for closures is bounded. An intermediate structure is employed to judge the validity of a subspace and compute closures more efficiently. Since the searching in subspaces are independent tasks, a parallel algorithm based on search space partition can be directly reached.
机译:概念格是形式概念分析中的核心数据结构,已被广泛用于机器学习,数据挖掘和知识发现,信息检索等。基于概念格的系统的主要困难来自于格构造本身。本文提出了一种基于闭包搜索空间分区的并行计算概念算法。该算法根据前面规定的标准将闭包搜索空间划分为几个子空间,并引入了一种有效的方案来识别有效的子空间,其中对闭包的搜索是有界的。采用中间结构来判断子空间的有效性并更有效地计算闭包。由于在子空间中的搜索是独立的任务,因此可以直接达到基于搜索空间分区的并行算法。

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