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Abstract: Discovery of association rules is an important database mining problem. Current algorithms for finding association rules require several passes over the analyzed database, and obviously the role of I/O overhead is very significant for very large databases. We present new algorithms that reduce the database activity considerably. The idea is to pick a random sample, to find using this sample all association rules that probably hold in the whole database, and then to verify the results with the... (Update)
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BibTeX entry: (Update)
H. Toivonen. Sampling large databases for association rules. In 22nd VLDB Conference, 1996. http://citeseer.ist.psu.edu/toivonen96sampling.html More
@inproceedings{ toivonen96sampling,
author = "Hannu Toivonen",
title = "Sampling Large Databases for Association Rules",
booktitle = "In Proc. 1996 Int. Conf. Very Large Data Bases",
month = "09",
publisher = "Morgan Kaufman",
editor = "T. M. Vijayaraman and Alejandro P. Buchmann and C. Mohan, and Nandlal L. Sarda",
% isbn = "",
pages = "134-145",
year = "1996",
url = "citeseer.ist.psu.edu/toivonen96sampling.html",
url = "citeseer.nj.nec.com/toivonen96sampling.html" }
Citations (may not include all citations):921 Mining association rules between sets of items in large data.. - Agrawal, Imielinski et al.
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