(Enter summary)
Abstract: We consider the problem of analyzing market-basket data and present several important contributions. First, we present a new algorithm for finding large itemsets which uses fewer passes over the data than classic algorithms, and yet uses fewer candidate itemsets than methods based on sampling. We investigate the idea of item reordering, which can improve the low-level efficiency of the algorithm. Second, we present a new way of generating "implication rules," which are normalized based on both... (Update)
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BibTeX entry: (Update)
Sergey Brin, Rajeev Motwani, Jeffrey D. Ullman, and Shalom Tsur. Dynamic itemset counting and implication rules for market basket data. SIGMOD Record (ACM Special Interest Group on Management of Data), 26(2):255, 1997. http://citeseer.ist.psu.edu/brin97dynamic.html More
@inproceedings{ brin97dynamic,
author = "Sergey Brin and Rajeev Motwani and Jeffrey D. Ullman and Shalom Tsur",
title = "Dynamic itemset counting and implication rules for market basket data",
booktitle = "SIGMOD 1997, Proceedings ACM SIGMOD International Conference
on Management of Data, May 13-15, 1997, Tucson, Arizona, USA",
month = "05",
publisher = "ACM Press",
editor = "Joan Peckham",
% isbn = "?",
pages = "255--264",
year = "1997",
url = "citeseer.ist.psu.edu/brin97dynamic.html",
url = "citeseer.nj.nec.com/brin97dynamic.html" }
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