16 citations · 26 across the 4 of their papers we have counts for
7 papers
RDD-Eclat: Approaches to Parallelize Eclat Algorithm on Spark RDD Framework (Extended Version)
Pankaj Singh, Sudhakar Singh, P K Mishra +1
Frequent itemset mining (FIM) is a highly computational and data intensive algorithm. Therefore, parallel and distributed FIM algorithms have been designed to process large volume…
RDD-Eclat: Approaches to Parallelize Eclat Algorithm on Spark RDD Framework
Pankaj Singh, Sudhakar Singh, P. K. Mishra +1
Initially, a number of frequent itemset mining (FIM) algorithms have been designed on the Hadoop MapReduce, a distributed big data processing framework. But, due to heavy disk I/O,…
A Data Structure Perspective to the RDD-based Apriori Algorithm on Spark
Pankaj Singh, Sudhakar Singh, P. K. Mishra +1
During the recent years, a number of efficient and scalable frequent itemset mining algorithms for big data analytics have been proposed by many researchers. Initially, MapReduce-b…
Mining Association Rules in Various Computing Environments: A Survey
Sudhakar Singh, Pankaj Singh, Rakhi Garg +1
Association Rule Mining (ARM) is one of the well know and most researched technique of data mining. There are so many ARM algorithms have been designed that their counting is a lar…
Performance Optimization of MapReduce-based Apriori Algorithm on Hadoop Cluster
Sudhakar Singh, Rakhi Garg, P K Mishra
Many techniques have been proposed to implement the Apriori algorithm on MapReduce framework but only a few have focused on performance improvement. FPC (Fixed Passes Combined-coun…
A Comparative Study of Association Rule Mining Algorithms on Grid and Cloud Platform
Sudhakar Singh, Rakhi Garg, P. K. Mishra
Association rule mining is a time consuming process due to involving both data intensive and computation intensive nature. In order to mine large volume of data and to enhance the…