article

Parallel and Distributed Association Mining: A Survey

Author:

Mohammed J. ZakiAuthors Info & Claims

IEEE Concurrency, Volume 7, Issue 4

Pages 14 - 25

https://doi.org/10.1109/4434.806975

Published: 01 October 1999 Publication History

Abstract

The author surveys the state of the art in parallel and distributed association-rule-mining algorithms and uncovers the field's challenges and open research problems. This survey can serve as a reference for both researchers and practitioners.

References

[1]

R. Agrawal, et al., "Fast Discovery of Association Rules," Advances in Knowledge Discovery and Data Mining, U. Fayyad et al., eds., AAAI Press, Menlo Park, Calif., 1996, pp. 307-328.

[2]

J.S. Park M. Chen and P.S. Yu, "An Effective Hash Based Algorithm for Mining Association Rules," Proc. ACM SIGMOD Conf., ACM Press, New York, 1995, pp. 175-186.

[3]

A. Savasere E. Omiecinski and S. Navathe, "An Efficient Algorithm for Mining Association Rules in Large Databases," Proc. 21st Int'l Conf. Very Large Databases, Morgan Kaufmann, San Francisco, 1995, pp. 432-444.

[4]

A. Mueller, Fast Sequential and Parallel Algorithms for Association Rule Mining: A Comparison, Tech. Report CS-TR-3515, Univ. of Maryland, College Park, Md., 1995.

Digital Library

[5]

S. Brin, et al., "Dynamic Itemset Counting and Implication Rules for Market Basket Data," Proc. ACM SIGMOD Conf. Management of Data, ACM Press, New York, 1997, pp. 255-264.

[6]

M.J. Zaki, et al., "New Algorithms for Fast Discovery of Association Rules," Proc. 3rd Int'l Conf. Knowledge Discovery and Data Mining, AAAI Press, Menlo Park, Calif., 1997, pp. 283-286.

[7]

J.S. Park M. Chen and P.S. Yu, "Efficient Parallel Data Mining for Association Rules," Proc. ACM Int'l Conf. Information and Knowledge Management, ACM Press, New York, 1995, pp. 31-36.

[8]

R. Agrawal and J. Shafer, "Parallel Mining of Association Rules," IEEE Trans. Knowledge and Data Eng., Vol. 8, No. 6, Dec. 1996, pp. 962-969.

Digital Library

[9]

T. Shintani and M. Kitsuregawa, "Hash Based Parallel Algorithms for Mining Association Rules," Proc. 4th Int'l Conf. Parallel and Distributed Information Systems, IEEE Computer Soc. Press, Los Alamitos, Calif., 1996, pp. 19-30.

[10]

E.-H. Han G. Karypis and V. Kumar, "Scalable Parallel Data Mining for Association Rules," Proc. ACM Conf. Management of Data, ACM Press, New York, 1997, pp. 277-288.

[11]

D. Cheung, et al. "A Fast Distributed Algorithm for Mining Association Rules," Proc. 4th Int'l Conf. Parallel and Distributed Information Systems, IEEE Computer Soc. Press, Los Alamitos, Calif., 1996, pp. 31-42.

[12]

D. Cheung and Y. Xiao, "Effect of Data Skewness in Parallel Mining of Association Rules," Proc. Pacific-Asia Conf. Knowledge Discovery and Data Mining, Lecture Notes in Computer Science, Vol. 1394, Springer-Verlag, New York, 1998, pp. 48-60.

[13]

M.J. Zaki, et al., "Parallel Data Mining for Association Rules on Shared-Memory Multi-Processors," Proc. Supercomputing '96, IEEE Computer Soc. Press, Los Alamitos, 1996.

[14]

D. Cheung K. Hu and S. Xia, "Asynchronous Parallel Algorithm for Mining Association Rules on Shared-Memory Multi-Processors," Proc. 10th ACM Symp. Parallel Algorithms and Architectures, ACM Press, New York, 1998, pp. 279-288.

[15]

M.J. Zaki, et al., "Parallel Algorithms for Fast Discovery of Association Rules," Data Mining and Knowledge Discovery: An Int'l J., Vol. 1, No. 4, Dec. 1997, pp. 343-373.

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Parallel and Distributed Association Mining: A Survey

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Published In

cover image IEEE Concurrency

IEEE Concurrency Volume 7, Issue 4

October 1999

96 pages

ISSN:1092-3063

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Copyright © Copyright © 1999 IEEE. All Rights Reserved.

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IEEE Educational Activities Department

United States

Publication History

Published: 01 October 1999

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Cited By

Kaur MSingh MSaini M(2024)Analyzing the relation among different factors leading to Ph.D. dropout using numerical association rule miningEducation and Information Technologies10.1007/s10639-023-12260-z29:1(375-399)Online publication date: 1-Jan-2024
https://dl.acm.org/doi/10.1007/s10639-023-12260-z
Fernandez-Basso CRuiz MMartin-Bautista M(2023)New Spark solutions for distributed frequent itemset and association rule mining algorithmsCluster Computing10.1007/s10586-023-04014-w27:2(1217-1234)Online publication date: 30-Apr-2023
https://dl.acm.org/doi/10.1007/s10586-023-04014-w
Shelar AKulkarni R(2022)Swarm of Honey Bees for Association Rule Mining Using CUDAInternational Journal of Software Innovation10.4018/IJSI.29799610:1(1-27)Online publication date: 6-May-2022
https://dl.acm.org/doi/10.4018/IJSI.297996
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HAMDAD LBENATCHBA K(2021)Association Rules MiningSN Computer Science10.1007/s42979-021-00819-x2:6Online publication date: 9-Sep-2021
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Berthold MFillbrunn ASiebes A(2021)Widening: using parallel resources to improve model qualityData Mining and Knowledge Discovery10.1007/s10618-021-00749-535:4(1258-1286)Online publication date: 1-Jul-2021
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