A Survey on Parallel Partition Prime Multiple Algorithm
Anjali Singla1, Jagpreet Kaur2
1Anjali Singla, Computer Science, Lovely Professional University, Phagwara, Punjab, India.
2Jagpreet Kaur, Computer Science, Lovely Professional University, Phagwara, Punjab, India.
Manuscript received on January 30, 2013. | Revised Manuscript received on February 17, 2013. | Manuscript published on February 28, 2013. | PP: 661-664 | Volume-2 Issue-3, February 2013.  | Retrieval Number: C1156022313/2013©BEIESP

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Abstract: One of the important problems in data mining research is discovering Association rules from databases of transactions, where each transaction contains a set of items. In this dissertation work and improved approach proposed for parallel association rule mining. I proposed a new parallel partition prime multiple algorithms for association rule mining. Partition prime multiple algorithm addresses the shortcoming of previously proposed parallel buddy prime algorithm. New efficient algorithm proposed for load balancing. The proposed algorithm for parallel frequent item set 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, Load Balancing Algorithm.