Mining Class Association Rules in Distributed Datasets

Nguyen Thi Thuy Loan, Đỗ Trung Tuấn, Nguyễn Hữu Ngự
Author affiliations

Authors

  • Nguyen Thi Thuy Loan Trường Cao đẳng Phát thanh - Truyền hình II
  • Đỗ Trung Tuấn Trường Đại học Khoa học Tự nhiên, Hà Nội
  • Nguyễn Hữu Ngự

DOI:

https://doi.org/10.15625/1813-9663/30/3/2842

Keywords:

CBA, CAR-Miner, class association rules, distributed, peer-to-peer network

Abstract

This paper proposes a method for mining class association rules in distributed datasets using peer-to-peer network. This method utilizes the computing performance of PCs in the network to process the local information at each site, and then only transfers the information of item sets that their supports satisfying the minimum support threshold to the mining site. Therefore, the proposed method can reduce the memory usage than that of transferring all dataset’s information to the mining site.

Metrics

Metrics Loading ...

Downloads

Published

25-08-2014

How to Cite

[1]
N. T. Thuy Loan, Đỗ T. Tuấn, and N. H. Ngự, “Mining Class Association Rules in Distributed Datasets”, JCC, vol. 30, no. 3, pp. 189–202, Aug. 2014.

Issue

Section

Computer Science