Distributed Mining of Association Rules Based on Privacy-Preserved Method

摘要：

With the rapid development of social information, the application of distributed database system is increasing. Distributed data mining will play an important role in data mining. As one of the wellknown distributed association rules mining algorithm, the FDM algorithm is very fast and efficient, however, the cost of this algorithm is very great because it is designed under the condition of nonshared resource. Moreover, the important information at every site is exposed to other sites, which is not accord to the nowadays trend of attaching importance to privacy preserving increasingly. In this paper, we propose an improved algorithm based on the FDM algorithm. In the process, it computes the total support count with the privacy-preserved method, meanwhile ensures the source of every local large item-set and local support count is covered, so it reduces the time spent on communication and preserves the privacy of the data distributed at each site. The experimental evaluations show that the proposed algorithm is efficient and rather suitable for the practical application fields.

关键词： FDM privacy preserving association rules data mining

作者: Hua-jin Wang Chun-an Hu Jian-sheng Liu

作者单位: School of Information Engineering Jiangxi University of Science and Technology Ganzhou, China School of Science Jiangxi University of Science and Technology Ganzhou, China

会议类型: 国际会议

会议名称: Third International Symposium on Information Science and Engineering(第三届信息科学与工程国际会议 ISISE 2010)

会议地点: 上海

会议语种:英文

页码: 494-497

在线出版日期: 2010-12-24（万方平台首次上网日期，不代表论文的发表时间）