70 citations · 148 across the 9 of their papers we have counts for
10 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…
Just-in-time Quantum Circuit Transpilation Reduces Noise
Ellis Wilson, Sudhakar Singh, Frank Mueller
Running quantum programs is fraught with challenges on on today's noisy intermediate scale quantum (NISQ) devices. Many of these challenges originate from the error characteristics…
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…