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Algorithms 2012, 5(4), 654-667; doi:10.3390/a5040654

Extracting Co-Occurrence Relations from ZDDs

Received: 27 September 2012 / Revised: 4 December 2012 / Accepted: 6 December 2012 / Published: 13 December 2012
(This article belongs to the Special Issue Graph Algorithms)
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Abstract: A zero-suppressed binary decision diagram (ZDD) is a graph representation suitable for handling sparse set families. Given a ZDD representing a set family, we present an efficient algorithm to discover a hidden structure, called a co-occurrence relation, on the ground set. This computation can be done in time complexity that is related not to the number of sets, but to some feature values of the ZDD. We furthermore introduce a conditional co-occurrence relation and present an extraction algorithm, which enables us to discover further structural information.
Keywords: BDD; ZDD; partition; co-occurrence; data mining BDD; ZDD; partition; co-occurrence; data mining
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Toda, T. Extracting Co-Occurrence Relations from ZDDs. Algorithms 2012, 5, 654-667.

AMA Style

Toda T. Extracting Co-Occurrence Relations from ZDDs. Algorithms. 2012; 5(4):654-667.

Chicago/Turabian Style

Toda, Takahisa. 2012. "Extracting Co-Occurrence Relations from ZDDs." Algorithms 5, no. 4: 654-667.

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