Superset generation on decision diagrams

Superset generation on decision diagrams
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决策图上的超集生成

DOI:
10.1007/978-3-319-15612-5_28
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发表时间:
2015
期刊:
Proc. 9th International Workshop on Algorithms and Computation (WALCOM 2015), Lecture Notes in Computer Science
影响因子:
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通讯作者:
Shin-ichi Minato
Shin-ichi Minato
中科院分区:
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文献类型:
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作者:
Takahisa Toda;Shogo Takeuchi;Koji Tsuda;Shin-ichi Minato

文献摘要

相似文献

从给定的集合族生成所有超集很重要,因为它与识别因果关系密切相关。本文提出了一种有效利用压缩数据结构 BDD 和 ZDD 来生成超集的有效方法。我们分析代表所有超集的 BDD 的大小。作为副产品,我们获得了 BDD 大小的一个重要上限,它表示固定变量排序中的单调布尔函数。
Generating all supersets from a given set family is important, because it is closely related to identifying cause-effect relationship. This paper presents an efficient method for superset generation by using the compressed data structures BDDs and ZDDs effectively. We analyze the size of a BDD that represents all supersets. As a by-product, we obtain a non-trivial upper bound for the size of a BDD that represents a monotone Boolean function in a fixed variable ordering.