Open AccessProceedings Article
An Efficient Algorithm for Mining Association Rules in Large Databases
Ashoka Savasere,Edward Omiecinski,Shamkant B. Navathe +2 more
- pp 432-444
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TLDR
This paper presents an efficient algorithm for mining association rules that is fundamentally different from known algorithms and not only reduces the I/O overhead significantly but also has lower CPU overhead for most cases.Abstract:
Mining for a.ssociation rules between items in a large database of sales transactions has been described as an important database mining problem. In this paper we present an efficient algorithm for mining association rules that is fundamentally different from known algorithms. Compared to previous algorithms, our algorithm not only reduces the I/O overhead significantly but also has lower CPU overhead for most cases. We have performed extensive experiments and compared the performance of our algorithm with one of the best existing algorithms. It was found that for large databases, the CPU overhead was reduced by as much as a factor of four and I/O was reduced by almost an order of magnitude. Hence this algorithm is especially suitable for very large size databases.read more
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References
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Proceedings ArticleDOI
Mining association rules between sets of items in large databases
TL;DR: An efficient algorithm is presented that generates all significant association rules between items in the database of customer transactions and incorporates buffer management and novel estimation and pruning techniques.
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Fast Algorithms for Mining Association Rules in Large Databases
Book
Knowledge Discovery in Databases
Gregory Piateski,William Frawley +1 more
TL;DR: Knowledge Discovery in Databases brings together current research on the exciting problem of discovering useful and interesting knowledge in databases, which spans many different approaches to discovery, including inductive learning, bayesian statistics, semantic query optimization, knowledge acquisition for expert systems, information theory, and fuzzy 1 sets.
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Parallel database systems: the future of high performance database systems
David J. DeWitt,Jim Gray +1 more
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Knowledge Discovery in Databases: An Attribute-Oriented Approach
TL;DR: An attribute-oriented induction method has been developed for knowledge discovery in databases that integrates a machine learning paradigm with set-oriented database operations and extracts generalized data from actual data in databases.