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Dynamic Data Mining: Exploring Large Rule Spaces by Sampling (1998) [4 citations — 1 self]

by Sergey Brin ,  Lawrence Page
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Abstract:

A great challenge for data mining techniques is the huge space of potential rules which can be generated. If there are tens of thousands of items, then potential rules involving three items number in the trillions. Traditional data mining techniques rely on downward-closed measures such as support to prune the space of rules. However, in many applications, such pruning techniques either do not sufficiently reduce the space of rules, or they are overly restrictive. We propose a new solution to this problem, called Dynamic Data Mining (DDM). DDM foregoes the completeness offered by traditional techniques based on downward-closed measures in favor of the ability to drill deep into the space of rules and provide the user with a better view of the structure present in a data set. Instead of a single determinstic run, DDM runs continuously, exploring more and more of the rule space. Instead of using a downward-closed measure such as support to guide its exploration, DDM uses a user-defined m...

Citations

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347 Dynamic itemset counting and implication rules for market basket data – Brin, Motwani, et al. - 1997
343 Beyond market baskets: Generalizing association rules to correlations – Brin, Motwani, et al. - 1997
279 Sampling large databases for association rules – Toivonen - 1996
204 New algorithms for fast discovery of association rules – Zaki, Parthasarathy, et al. - 1997
182 Mining association rules with item constraints – Srikant, Vu, et al.
167 Parallel mining of association rules – Agrawal, Shafer - 1996
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78 SWIG: An easy to use tool for integrating scripting languages with – BEAZLEY - 1996
61 Efficient mining of association rules in distributed databases – Cheung, Ng, et al. - 1996
55 Fast Sequential and Parallel Algorithm for Association Rule Mining: A Comparison – Mueller - 1995
50 Parallel mining of association rules: Design, implementation and experience – Agrawal, Shafer - 1996
40 A new framework for itemset generation – Aggarwal, Yu - 1998
10 Visualization Techniques to Explore Data Mining Results for Document Collections – Feldman, Klosgen, et al. - 1997