Descending Dimension Algorithm for Association Rules Based on SQL Calculation

Qing Yun Chi; Zhen Hao; Xiu Ying Jiang

doi:10.4028/www.scientific.net/AMM.602-605.3626

Paper Titles

Comparison of Particle Swarm Algorithm and Ant Colony Algorithm in the Optimization of Uniform Quantizer
p.3608

Research on the Optimization Scheme of Base Station Construction Based on Artificial Bee Colony Algorithm
p.3612

The Reduction of a Type of Singular Partial Differential Equations
p.3616

Research on Brain Drain of Energy Environmental Protection Enterprises Based on Evolutionary Game Model
p.3620

Descending Dimension Algorithm for Association Rules Based on SQL Calculation
p.3626

User Interface Design and Implementation for Electricity Operation Information System Based on Android
p.3630

A Layer Segmentation Based Compression Algorithm
p.3635

Study of Cognitive Radio Spectrum Sensing Algorithm Based on Compressed Sensing
p.3639

Deployment Strategy in Distributed Underwater Sensor Networks
p.3643

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Descending Dimension Algorithm for Association...

Descending Dimension Algorithm for Association Rules Based on SQL Calculation

Abstract:

Apriori algorithm is a classical algorithm for association rules mining. But the algorithm must be connect repeatly and operate steps layer by layer to find frequent item sets. To overcome the shortcomings of Apriori algorithm, relational database language SQL is used proceed from the higher-order item sets and compute the support of item set to find frequent item sets in this paper. The solution process eliminates a large number of duplicate items produced by the connection from low-dimensional to high-dimensional in the traditional process. The calculation is simplified and efficiency improved.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

3626-3629

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.3626

Citation:

Cite this paper

Online since:

August 2014

Authors:

Qing Yun Chi*, Zhen Hao, Xiu Ying Jiang

Keywords:

Aprior, Association Rule, Data Mining (DM), SQL

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] YOU Lei, LAN Yang, XIONG Yan. An Optimized Apriori Implementation Based on Relational Algebra,. Journal of Xinyang Normal University, 23, 156-158, (2011).

Google Scholar

[2] Zhanjiang, WANG Zhi-He, JING Yong-Xia. An Algorithm of Frequent Pattern Mining based on SQL,. JOURNAL OF ZHONGYUAN INSTITUTE OF TECHNOLOG, 16, 48-52, (2005).

Google Scholar

[3] Jiawei Han, Michelins. Data Mining Concepts and Techniques,. (2001).

Google Scholar

[4] Csaba Istv´an Sidl´, Andr´as Luk´acs. Shaping SQL-Based Frequent Pattern Mining Algorithms.

Google Scholar

[5] ZHAO Jian-song, CHEN Zai-ping. The research of improved Apriori algorithm based on SQL, Journal of Tianjin University of Technology. (2009).

Google Scholar

[6] Abdullah Alashqur. RDB-MINER. A SQL-Based Algorithm for Mining True Relational Databases, JOURNAL OF SOFTWARE. (2010).

DOI: 10.4304/jsw.5.9.998-1005

Google Scholar

[7] R. Elmasri and S. Navaho. Fundamentals of Database Systems, Fifth Edition, Addison-Wesley. (2007).

Google Scholar