An Approach to Mine Frequent Itemsets in Cloud Using Apriori and FP-tree Approach

Abstract
Authors
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References

Cloud computing has become a big name in present era. It has proved to be a great solution for storing and processing huge amount of data. It provides us demand, scalable, pay-as-you go compute and storage capacity. Data mining techniques implemented with cloud computing paradigm are very useful to analyze big data on clouds. In our dissertation we have used association rule mining as a data mining technique. In particular we have used Apriori algorithm for association rule mining. It has been observed that the original Apriori algorithm was designed for sequential computation so directly using it for parallel computation doesn’t seems a good idea. So we have improved the Apriori algorithm (FP Growth) so as to suit it for parallel computation platform. We have used CloudSim Simulator for cloud computing.

Published In : IJCAT Journal Volume 1, Issue 7

Date of Publication : 31 August 2014

Pages : 387 - 389

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Publication Link : An Approach to Mine Frequent Itemsets in Cloud Using Apriori and FP-tree Approach

Harneet Khurana : Research Scholar, is pursuing M.Tech in Computer Science and Engineering in Patiala Institute of Engineering And Technology for Women, Patiala, Punjab, India.

Kailash Bahl : Dean Academics in Patiala Institute Of Engineering and Technology for Women, Patiala, Punjab, India.

Data Mining

Cloud Computing

Association Rule Mining in Clouds

Apriori Algorithm

FP-Growth Algorithm

Cloud computing is an architecture which is known for its powerful capability of computation and storage and resource sharing. These features make cloud computing favorable to data mining service in network environment. We have discussed association rule mining in cloud environment and various parallel and distributed mining algorithms. Data mining on cloud computing paradigm can benefit us to a great extent. That is why we have implemented data mining technique on cloud platform. Out of many data mining techniques we have studied association rule mining technique in this paper. More specifically we have association

[1] Jiawei Han Micheline Kamber, Data Mining concepts and techniques, 2nd Ed.

[2] Sanjeev Rao, Priyanka Gupta, ?Implementing Improved Algorithm Over APRIORI Data Mining Association Rule Algorithm?, ISSN: 0976-8491 (Online) | ISSN: 2229-4333 (Print) IJCST Vol. 3, Issue 1, Jan. - March 2012.

[3] Bhagyashree Ambulkar, Vaishali Borkar, ?Data Mining in Cloud Computing?, Proceedings published by International Journal of Computer Applications® (IJCA)ISSN: 0975 – 8887.

[4] Deepak Garg et. al. “Comparative Analysis of Various Approaches Used in Frequent Pattern Mining” (IJACSA) International Journal of Advanced Computer Science and Applications, Special Issue on Artificial Intelligence.

[5] Han J. and M. Kamber, “Data Mining Concepts and Techniques”, Morgan Kaufmann publishers, 2nd Edition.

[6] Jing Ding, Shanlin Yang, ?Classification Rules Mining Model with Genetic Algorithm in Cloud Computing?, International Journal of Computer Applications (0975 – 888), Volume 48– No.18, June 2012.

[7] Goswami D.N et. al. “An Algorithm for Frequent Pattern Mining Based On Apriori ” (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 04, 2010, Pp. 942-947.

[8] Yunhong Gu and Robert L. Grossman “Sector and Sphere: The Design and Implementation of a High Performance Data Cloud”.

[9] Ramakrishnan Srikant and Rakesh Agrawal “Mining Generalized Association Rules”.

[10] M. Bramer. Principles of Data Mining. Springer, 2007.