Paper
12 March 2002 Study and improvement on hierarchical algorithm of association rule
Luo Zhong, Hongxia Xia, Jingling Yuan
Author Affiliations +
Abstract
This paper introduces the problem of data mining association rules. We adopt the iterative method to enlarge the size of the item set gradually and describe the hierarchical algorithm in detail. The hierarchical algorithm produces a larger provisional sets based on the obtained frequent item sets and make sure that those provisional sets which will never be frequent item set are ignored under the premise of the known information. Finally, an improving algorithm which is to combine the last several procedures of iteration into a single scan of the database D. Mainly because that the more backwards the iterative processes approach the end, the less the provisional sets are there.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Luo Zhong, Hongxia Xia, and Jingling Yuan "Study and improvement on hierarchical algorithm of association rule", Proc. SPIE 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, (12 March 2002); https://doi.org/10.1117/12.460215
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Databases

Data mining

Evolutionary algorithms

Mining

Iterative methods

Artificial intelligence

Information technology

RELATED CONTENT

A topological-based spatial data clustering
Proceedings of SPIE (April 20 2016)
A data mining algorithm based on the rough sets theory...
Proceedings of SPIE (December 02 2005)
Incremental information mining
Proceedings of SPIE (March 12 2002)
Decomposition in data mining: a medical case study
Proceedings of SPIE (March 27 2001)
Theoretical sampling for data mining
Proceedings of SPIE (April 06 2000)

Back to Top