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Extracting Co-Occurrence Relations from ZDDs
ERATO, MINATO Discrete Structure Manipulation System Project, JST, Sapporo-Shi 060-0814, Japan
Received: 27 September 2012; in revised form: 4 December 2012 / Accepted: 6 December 2012 / Published: 13 December 2012
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
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MDPI and ACS Style
Toda, T. Extracting Co-Occurrence Relations from ZDDs. Algorithms 2012, 5, 654-667.
Toda T. Extracting Co-Occurrence Relations from ZDDs. Algorithms. 2012; 5(4):654-667.
Toda, Takahisa. 2012. "Extracting Co-Occurrence Relations from ZDDs." Algorithms 5, no. 4: 654-667.