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Abstract: Association rule mining recently attracted strong attention. Usually, the classification hierarchy over the data items is available. Users are interested in generalized association rules that span different levels of the hierarchy, since sometimes more interesting rules can be derived by taking the hierarchy into account. In this paper, we propose the new parallel algorithms for mining association rules with classification hierarchy on a shared-nothing parallel machine to improve its... (Update)
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BibTeX entry: (Update)
Takahiko Shintani and Masaru Kitsuregawa. Parallel mining algorithms for generalized association rules with classification hierarchy. SIGMOD Record (ACM Special Interest Group on Management of Data), 27(2):25--36, 1998. http://citeseer.ist.psu.edu/shintani98parallel.html More
@inproceedings{ shintani98parallel,
author = "Takahiko Shintani and Masaru Kitsuregawa",
title = "Parallel mining algorithms for generalized association rules with classification hierarchy",
pages = "25--36",
year = "1998",
url = "citeseer.ist.psu.edu/shintani98parallel.html" }
Citations (may not include all citations):910 Fast algorithms for mining association rules - Agrawal, Srikant - 1994
268 Mining generalized association rules - Srikant, Agrawal - 1995
157 Mining sequential patterns: Generalizations and performance .. - Srikant, Agrawal - 1996
115 Scalable parallel data mining for association rules - Han, Karypis et al. - 1997
56 Parallel mining of association rules - Agrawal, Shafer - 1996
52 A fast distributed algorithms for mining association rules - Cheung, Han et al. - 1996
34 Efficient parallel data mining for association rules (context) - Park, Chen et al. - 1995
30 Efficient mining of association rules in distributed databas.. - Cheung, Ng et al. - 1996
25 Hash based parallel algorithms for mining association rules - Shintani, Kitsuregawa - 1996
8 Mining algorithms for sequential patterns in parallel : Hash.. - Shintani, Kitsuregawa - 1998
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