Due to the advancement in internet technologies the volume of data is tremendously increasing day by day. The research is gaining importance in extracting valuable information from such huge amount of data. Many research works are done and various algorithms are proposed. The PrePost algorithm is one of well-known algorithms of frequent pattern mining. It is based on N-list data structure to mine frequent item-sets. But the performance of PrePost algorithm degrades when it comes to processing of large amount of data. Hadoop is very well known technique for processing such large amount of data. This paper proposes the Improved PrePost algorithm which combines the features of Hadoop in order to process large data efficiently. Efficiency of PrePost algorithm is enhanced by implementing compact PPC tree with the general tree method and finding frequent itemsets without generating candidate itemsets. An architecture of the Improved PrePost algorithm with public cloud is proposed. The results show that as dataset size is increased, the Improved PrePost algorithm gives 60% better performance.
An improved Prepost algorithm with hadoop platform proposed by Thakare et al. REF .
An Improved PrePost Algorithm for Frequent Pattern Mining with Hadoop on Cloud
Procedia Computer Science
Computer Science