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A New Parallel Prime Multi Algorithm for Association Rule Mining


Affiliations
1 School of Information Technology, Rajiv Gandhi Technological University, Bhopal (M.P.), India
2 Samrat Ashok Technological Insitute (Degree), Vidisha (M.P.), India
     

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This paper describes a new parallel PrimeMulti algorithm for association rule mining. PrimeMulti algorithm addresses the shortcoming of previously proposed parallel buddy prima algorithm. New efficient algorithm for load balancing is also proposed in this paper. New algorithm divide transaction database equally according to the transaction length to the processors. In the Parallel PrimeMulti algorithm transaction database is represented by prime number. Less memory is requires as each transaction is replaced with the product of the equivalent prime numbers of their items. Parallel PrimeMulti algorithm works on top down as well as bottom up approach. The proposed algorithm for parallel frequent itemset mining and load balancing reduces the time and data complexity and divide transactional database efficiently for good load balancing among the processor.

Keywords

Association Rule Mining, Confidence, Frequent Item Set, Parallel Data Mining, Top-Down Approach, Support.
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  • A New Parallel Prime Multi Algorithm for Association Rule Mining

Abstract Views: 260  |  PDF Views: 2

Authors

Jitendra Agrawal
School of Information Technology, Rajiv Gandhi Technological University, Bhopal (M.P.), India
R. C. Jain
Samrat Ashok Technological Insitute (Degree), Vidisha (M.P.), India

Abstract


This paper describes a new parallel PrimeMulti algorithm for association rule mining. PrimeMulti algorithm addresses the shortcoming of previously proposed parallel buddy prima algorithm. New efficient algorithm for load balancing is also proposed in this paper. New algorithm divide transaction database equally according to the transaction length to the processors. In the Parallel PrimeMulti algorithm transaction database is represented by prime number. Less memory is requires as each transaction is replaced with the product of the equivalent prime numbers of their items. Parallel PrimeMulti algorithm works on top down as well as bottom up approach. The proposed algorithm for parallel frequent itemset mining and load balancing reduces the time and data complexity and divide transactional database efficiently for good load balancing among the processor.

Keywords


Association Rule Mining, Confidence, Frequent Item Set, Parallel Data Mining, Top-Down Approach, Support.