Abstract
The paper proposed a parallel algorithm for mining association rules based on FP-tree, namely, PAMARF algorithm. It distributed data according horizontal projection method. PAMARF algorithm made nodes compute local frequent itemsets with FP-tree, then the centre node exchanged data with other nodes and combined, finally, global frequent itemsets were gained. PAMARF algorithm required far less communication traffic by the strategy of top-down. Theoretical analysis and experimental results suggest that PAMARF algorithm is effective.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Han, J., Kamber, M.: Data Mining: Concepts and Techniques. High Educattion Press, Beijing (2001)
Agrawal, R., Srikant, R.: Fast algorithms for mining frequent itemsets. In: Proceedings of the 20th International Conference Very Large DataBase, Santiago, Chile, pp. 487–499 (1994)
Park, J.S., Chen, M.S., Yu, P.S.: Efficient distributed data mining for frequent itemsets. In: Proceedings of the 4th International Conference on Information and Knowledge Management, Baltimore, Maryland, pp. 31–36 (1995)
Agrawal, R., Shafer, J.C.: Distributed mining of frequent itemsets. IEEE Transaction on Knowledge and Data Engineering 8(6), 962–969 (1996)
Cheung, D.W., Han, J.W., Ng, W.T., Tu, Y.J.: A fast distributed algorithm for mining association rules. In: Proceedings of IEEE 4th International Conference on Management of Data, Miami Beach, Florida, pp. 31–34 (1996)
Han, J.W., Pei, J., Yin, Y.: Mining frequent patterns without Candidate Generation. In: Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data, pp. 1–12. ACM Press, New York (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Tu, F., He, B. (2011). A Parallel Algorithm for Mining Association Rules Based on FP-tree. In: Lin, S., Huang, X. (eds) Advances in Computer Science, Environment, Ecoinformatics, and Education. CSEE 2011. Communications in Computer and Information Science, vol 217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23339-5_73
Download citation
DOI: https://doi.org/10.1007/978-3-642-23339-5_73
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-23338-8
Online ISBN: 978-3-642-23339-5
eBook Packages: Computer ScienceComputer Science (R0)