Yeon-Dae Kwon, Yasunori ISHIHARA, Shougo SHIMIZU, Minoru ITO  Home/Search
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Abstract: this paper, we introduce the notion of (k; c)-sparsity, which is strictly weaker than the k-sparsity in our previous work. The value of c represents a degree of sparsity. Using (k; c)- sparsity, we propose a larger subclass of databases for which we can still eciently nd all the large itemsets. Next, we propose alternative measures to the support. For each measure, an itemset is called highly co-occurrent if the value indicating the correlation among the items exceeds a given threshold. In... (Update)
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BibTeX entry: (Update)
@article{ kwon00computational,
author = "Kwon and Ishihara and Shimizu and Ito",
title = "Computational Complexity of Finding Highly Co-occurrent Itemsets in Market Basket Databases",
journal = "TIEICE: IEICE Transactions on Communications/Electronics/Information and Systems",
year = "2000",
url = "citeseer.ist.psu.edu/kwon00computational.html" }
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