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Fast algorithm for discovering maximum frequent itemsets of association rules

LIU Da-you^1,2, LIU Ya-bo^1,2, YIN Zhi-dong³

1. College of Computer Science and Technology, Jilin University, Changchun 130012, China；2. Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University,Changchun 130012, China； 3. Jilin Entry-Exit Inspection and Quarantine Bureau, Changchun 130062, China

Received:2003-09-28 Revised:1900-01-01 Online:2004-04-26 Published:2004-04-26
Contact: LIU Ya-bo

Abstract

Abstract: The present paper presents an efficient algorithm that improves set-enumeration tree and finds maximum frequent itemsets. By combining bottom-up and top-down searches in set-enumeration tree and making use of th e infrequent itemsets to prune candidates of the maximum frequent itemsets, the algorithm reduces the number of candidates of the maximum frequent itemsets gene rated by it so that the efficiency is increased.

Key words: association rule, set-enumeration tree, maximum freque nt itemset

CLC Number:

TP311

LIU Da-you, LIU Ya-bo, YIN Zhi-dong. Fast algorithm for discovering maximum frequent itemsets of association rules[J].J4, 2004, 42(02): 212-215.

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Fast algorithm for discovering maximum frequent itemsets of association rules

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