Main Reference PaperFiDoop-DP: Data Partitioning in Frequent Itemset Mining on Hadoop Clusters, IEEE Transactions on Parallel and Distributed Systems, 2016 [Java/Hadoop]
  • This paper proposes a strategy to mitigate high communication and reduce computing cost in MapReduce-based FIM algorithms, the developed FiDoop-DP, which exploits correlation among transactions to partition a large dataset across data nodes in a Hadoop cluster.

+ Description
  • This paper proposes a strategy to mitigate high communication and reduce computing cost in MapReduce-based FIM algorithms, the developed FiDoop-DP, which exploits correlation among transactions to partition a large dataset across data nodes in a Hadoop cluster.

  • To improve the performance of Frequent Itemset Mining on Hadoop clusters.

  • To eliminate the redundant transactions.

  • To mitigate communication overhead.

  • Reducing computing cost.

+ Aim & Objectives

  • To improve the performance of Frequent Itemset Mining on Hadoop clusters.

  • To eliminate the redundant transactions.

  • To mitigate communication overhead.

  • Reducing computing cost.

  • To further reduce the computation cost and communication overhead in big data, in addition to similarity computation with includes importance to frequency of items.

+ Contribution
  • To further reduce the computation cost and communication overhead in big data, in addition to similarity computation with includes importance to frequency of items.

  • Java JDK 1.8, Hadoop 1.2.1

  • Netbeans 8.0.1, J2SE, Hadoop

+ Software Tools & Technologies
  • Java JDK 1.8, Hadoop 1.2.1

  • Netbeans 8.0.1, J2SE, Hadoop

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-Depending on the complexity of the project and requirements.

Professional Ethics: We S-Logix would appreciate the students those who willingly contribute with atleast a line of thinking of their own while preparing the project with us. It is advised that the project given by us be considered only as a model project and be applied with confidence to contribute your own ideas through our expert guidance and enrich your knowledge.