计算机科学与探索Issue(12)：1494-1501,8.DOI:10.3778/j.issn.1673-9418.1408010
基于粗糙模糊集的不确定数据流聚类算法��
Clustering Algorithm over Uncertain Data Streams Based on Rough Fuzzy Set
摘要
Abstract
To solve data streams clustering problems of high dimensionality and high uncertainty level, this paper proposes an algorithm named HFMicro. The rough fuzzy set theory is introduced to define a new uncertain model of data streams, and the upper and lower approximations of the membership degree are used to describe micro-clusters. The most suitable micro-clusters are selected according to the similarity degree between rough fuzzy sets. Dynamic window of decay model is applied to achieve good algorithmic efficiency and clustering performance. Offline clus-tering model makes the algorithm have good real-time performance. The experimental results show that the algo-rithm can handle the data streams with high dimensionality and uncertainty level, and can process the data streams having existent uncertainty and property uncertainty at the same time. In comparison with the existing algorithms, HFMicro has better performance.关键词
不确定数据流/粗糙模糊集/聚类/隶属度Key words
uncertain data streams/rough fuzzy set/clustering/membership degree分类
信息技术与安全科学引用本文复制引用
姜元凯,郑洪源..基于粗糙模糊集的不确定数据流聚类算法��[J].计算机科学与探索,2014,(12):1494-1501,8.基金项目
The Union Innovation Fund Projects of Jiangsu Province under Grant No. SBY201320423(江苏省产学研联合创新资金项目) （江苏省产学研联合创新资金项目）
