Extracting Co-Occurrence Relations from ZDDs
Copyright policy )Extracting Co-Occurrence Relations from ZDDs
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.
- Japan Science and Technology Agency Japan
- Hokkaido Bunkyo University Japan
- Hokkaido University Japan
Data structures, Industrial engineering. Management engineering, Learning and adaptive systems in artificial intelligence, QA75.5-76.95, data mining, T55.4-60.8, partition, ZDD, Electronic computers. Computer science, co-occurrence, Nonnumerical algorithms, BDD
Data structures, Industrial engineering. Management engineering, Learning and adaptive systems in artificial intelligence, QA75.5-76.95, data mining, T55.4-60.8, partition, ZDD, Electronic computers. Computer science, co-occurrence, Nonnumerical algorithms, BDD
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