不确定性数据的聚类分析研究及应用

Application and research of analysis cluestering based on uncertain data

对近年来不确定性数据聚类算法的研究现状与进展进行总结。首先对较有代表性的聚类算法,从思想、关键技术和优缺点等方面进行分析。其次选用数据集对基于密度的算法进行测试和对比分析。并给出基于不确定性数据的聚类算法,上述工作将为不确定数据管理提供有益的参考。

The classic algorithm of analysis clustering basing on uncertain data is discussed.The research actuality and new progress in uncertain data clustering algorithm in recent years are summarized in this paper.First,the analysis and induction of some representative uncertain data clustering algorithms have been made from several aspects,such as the ideas of algorithm,key technology,advantage and disadvantage.Second,several typical density-based algorithms and known data sets are selected;experiments are implemented and comparing with the same clustering of the data set under different algorithms.The clustor analysis was given by basing on compareding uncertain data in this paper.The above work can give a valuable reference for management of uncertain data.