Main Reference PaperPPHOPCM: Privacy-preserving High-order Possibilistic c-Means Algorithm for Big Data Clustering with Cloud Computing, IEEE Transactions on Big Data, May 2017 [Java].
  • A Privacy-Preserving a High-Order Possibilistic C-Means HOPCM algorithm (PPHOPCM) is proposed that performs efficient for big data clustering based on MapReduce. It applies polynomial functions for membership matrix and clustering centers.

+ Description
  • A Privacy-Preserving a High-Order Possibilistic C-Means HOPCM algorithm (PPHOPCM) is proposed that performs efficient for big data clustering based on MapReduce. It applies polynomial functions for membership matrix and clustering centers.

  • To improve the efficiency of big data clustering.

  • To develop privacy-preserving clustering algorithm.

+ Aim & Objectives
  • To improve the efficiency of big data clustering.

  • To develop privacy-preserving clustering algorithm.

  • Clustering centers are fixed based on certain approach instead of fixing it randomly at the initial stage..

+ Contribution
  • Clustering centers are fixed based on certain approach instead of fixing it randomly at the initial stage..

  • Java JDK 1.8, MySQL 5.5.40, Hadoop 1.2.1.

  • Netbeans 8.0.1, & J2EE.

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40, Hadoop 1.2.1.

  • Netbeans 8.0.1, & J2EE.

  • 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.

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