计算机技术与发展2017，Vol.27Issue(5)：102-107,6.DOI:10.3969/j.issn.1673-629X.2017.05.022
基于k-匿名的多源数据融合算法研究
Research on Data Fusion Algorithm for Multi-party Based on k-anonymity
摘要
Abstract
In today's network environment,data has become more and more important.Data integration technology can make the effective data integration for different data providers,and provide customized service for the customers.Data fusion technology usually adopts the top-down to choose candidates for updating data in each round,and with the increase of amount of data,this kind of method costs a lot of time,which is difficult to meet the time requirements of data fusion.In order to reduce the cost in the process of data fusion and improve the accuracy of data integration for multi-party,a multi-party data fusion algorithm based on k-anonymous combining with the top-to-down TDS algorithm and the attribute classification tree has been proposed.Simulation experiments have been conducted with Adult set of GUI as well as comparison of accuracy of data fusion with complexity.The experimental results show that the proposed algorithm has taken less time and effectively achieve ideal accuracy of data fusion.关键词
数据融合/k-匿名/自顶向下分类树/属性分类树Key words
data integration/k-anonymous/top-to-down TDS/attribute classification tree分类
信息技术与安全科学引用本文复制引用
杨月平,王箭..基于k-匿名的多源数据融合算法研究[J].计算机技术与发展,2017,27(5):102-107,6.基金项目
中国博士后科学基金(2014M561644) （2014M561644）
江苏省博士后科学基金(1402034C) （1402034C）
