By Suzuki E. (Ed), Arikawa S. (Ed)
This booklet constitutes the refereed lawsuits of the seventh overseas convention on Discovery technology, DS 2004, held in Padova, Italy in October 2004.The 20 revised lengthy papers and the nineteen revised typical papers awarded have been rigorously reviewed and chosen from eighty submissions. The papers are equipped in topical sections on development mining, type, outlier detection, clustering, function development and new release, wisdom acquisition, discovery technology in fact, computing device studying algorithms, net mining, purposes of predictive tools, and interdisciplinary techniques.
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Additional info for Discovery Science: 7th International Conference, DS 2004, Padova, Italy, October 2-5, 2004, Proceeindgs
Section 5 describes several improvements for practical use. Section 6 18 Takeaki Uno et al. presents experimental results of our algorithm and improvements on synthesis and realworld datasets. We conclude the paper in Section 7. 2 Preliminaries We give basic definitions and results on closed pattern mining according to [1,13,6]. Let be the set of items. A transaction database on is a set such that each is included in Each is called a transaction. , A subset P of is called a pattern (or itemset).
Therefore our algorithms are both time and space efficient in practice. 38 3 Shunsuke Inenaga et al. Algorithms In this section we present our efficient algorithms to solve Problem 1 for Boolean functions Let where The algorithms calculate scores for all possible pattern pairs, and output a pattern pair of the highest score. 1 Algorithm for Single Patterns For a single pattern, we need to consider only patterns of form where is a node in the GST for S: If a pattern has a corresponding path that ends in the middle of an edge of the GST, it will match the same set of strings as the pattern corresponding to the end node of that same edge, and hence the score would be the same.
O. jp Abstract. We consider the problem of discovering the optimal pair of substring patterns with bounded distance from a given set S of strings. We study two kinds of pattern classes, one is in form that are interpreted as cooperative patterns within distance, and the other is in form representing competing patterns, with respect to S. We show an efficient algorithm to find the optimal pair of patterns in time using O(N) space. We also present an time and space solution to a more difficult version of the optimal pattern pair discovery problem, where denotes the number of strings in S.
Discovery Science: 7th International Conference, DS 2004, Padova, Italy, October 2-5, 2004, Proceeindgs by Suzuki E. (Ed), Arikawa S. (Ed)