An improved Apriori-based algorithm for association rules mining

Authors:
Huan Wu;Zhigang Lu;Lin Pan;Rongsheng Xu;Wenbao Jiang
Affiliations:
Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China;Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China;Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China;Computing Center, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing, China;School of Information Management, Beijing Information Science & Technology University, Beijing, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 2
Year:
2009

Citing 6
Cited 0

Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Fast Algorithms for Mining Association Rules in Large Databases

VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
T-Trees, Vertical Partitioning and Distributed Association Rule Mining

ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Hash Partitioned apriori in Parallel and Distributed Data Mining Environment with Dynamic Data Allocation Approach

ICCSIT '08 Proceedings of the 2008 International Conference on Computer Science and Information Technology
An Efficient Frequent Patterns Mining Algorithm Based on Apriori Algorithm and the FP-Tree Structure

ICCIT '08 Proceedings of the 2008 Third International Conference on Convergence and Hybrid Information Technology - Volume 01
An Algorithm to Improve the Effectiveness of Apriori

COGINF '07 Proceedings of the 6th IEEE International Conference on Cognitive Informatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Because of the rapid growth in worldwide information, efficiency of association rules mining (ARM) has been concerned for several years. In this paper, based on the original Apriori algorithm, an improved algorithm IAA is proposed. IAA adopts a new count-based method to prune candidate itemsets and uses generation record to reduce total data scan amount. Experiments demonstrate that our algorithm outperforms the original Apriori and some other existing ARM methods.