Paper Title:
Improved Methods on Association Rules Mining Algorithms
  Abstract

Among the many mining algorithms of association rules, Apriori Algorithm is a classical algorithm that has caused the most discussion; it can effectively carry out the mining association rules. However, based on Apriori Algorithm, most of the traditional algorithms exist "item sets generation bottleneck" problem, and are very time-consuming. An enhanced algorithm associating Apriori with transaction reduction and item reduction technique is put forward by the paper, in the algorithm candidate item sets generation and the support calculation are created after each transaction is compressed and connected, and the key word identifying is adopted in the candidate set, thus the process of pruning and string pattern matching is removed from Apriori algorithm. Original algorithm and improved algorithm implementation steps are presented by examples, the results show that the new algorithm reduces the storage space, improve the efficiency of the algorithm and improve the performance of data mining technology.

  Info
Periodical
Key Engineering Materials (Volumes 460-461)
Edited by
Yanwen Wu
Pages
148-152
DOI
10.4028/www.scientific.net/KEM.460-461.148
Citation
Y. S. He, J. F. Xiao, "Improved Methods on Association Rules Mining Algorithms", Key Engineering Materials, Vols. 460-461, pp. 148-152, 2011
Online since
January 2011
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Price
$32.00
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