Authors: Haruya Iwasaki, Shin-ichi Minato, and Thomas Zeugmann
Source: The IEICE Transactions on Information and Systems (Japanese Edition) (電子情報通信学会論文誌) Vol. J91-D, No. 3, 2008, 608 - 618.
Abstract. Recently, an efficient method of database analysis using Zero-suppressed Binary Decision Diagrams (ZBDDs) has been proposed. BDDs are a graph-based representation of Boolean functions, now widely used in system design and verification. Here we focus on ZBDDs, a special type of BDDs, which are suitable for handling large-scale combinatorial itemsets in transaction databases. The ZBDD size greatly depends on the variable ordering used. In this paper, we propose a new method of ZBDD variable ordering for itemset mining of large-scale transaction databases, and show experimental results.
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