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引用次数: 1

摘要

从海量异构数据集中获取可操作信息的自动化和半自动化系统对于许多应用程序至关重要。为了赢得我们的信任,这些系统的推理必须尽可能清晰。格已经开始在计算机科学中发挥关键作用,在分布式计算、编程语言、并发理论和数据挖掘中得到应用,从而证明了G. C. Rota关于格理论将在21世纪数学中发挥重要作用的信念[1]。在某些情况下,研究人员必须处理不一定是格的偏序集,问题是如何将这些偏序集嵌入到格中。回答这个问题的一个经典方法是构造晶格的MacNeille补全,这是将偏序集嵌入晶格的最紧凑的方法。1973年,G. Markowsky在他的论文中引入了不可约构造的序集,并证明了这是一种非常紧凑的表示格的方法。此外,不可约偏集具有G. Birkhoff在其著作[2]中引入的分配格的联合不可约偏集的许多性质。在本文中,我们给出了如何有效地构造一个微集的不可约微集的MacNeille补全。最后给出了这些思想的一些应用。
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Lattice Data Analytics: The Poset of Irreducibles and the MacNeille Completion
Automated and semi-automated systems that derive actionable information from massive, heterogeneous datasets are essential for many applications. The reasoning of such systems must be as clear as possible in order to earn our trust. Lattices have begun to play a key role in computer science finding applications in distributed computing, programming languages, concurrency theory, and data mining, thereby justifying G. C. Rota's belief that lattice theory will play an important role in 21st Century mathematics [1]. In some instances, researchers must deal with posets that are not necessarily lattices and the question arises how these posets can be embedded in lattices. A classic way to answer this question is to construct the MacNeille completion of the lattice, which is the most compact way to embed a poset into a lattice. In 1973 G. Markowsky introduced the poset of irreducibles construction in his dissertation and demonstrated that this was a very compact way to represent a lattice. In addition, the poset of irreducibles has many of the properties of the poset of join-irreducibles of distributive lattices that was introduced by G. Birkhoff and described in his book [2]. In this paper, we show how to construct the poset of irreducibles for the MacNeille completion of a poset efficiently. We conclude with some applications of these ideas.
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