文章基本信息

标题：Adaptive Trace of Multi-dimensional Clusters by Monitoring Data Streams
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作者：Nam Hun Park ; Kil Hong Joo2 ; Su Young Han 等
期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2013
卷号：8
期号：3
出版社：SERSC
摘要：In recent years, clustering data streams has been actively proposed in the field of data mining. In real-life domains, clustering methods for data streams should effectively monitor the continuous change of a data stream with respect to all the dimensions of the data stream. In this paper, a clustering method with frequency prediction of data elements is proposed. The incoming statistics of data elements in the monitoring range are maintained. For the range of elements with high density, the range is partitioned to detect the detailed boundary of clusters. To identifying the recent change of a data stream quickly, the support of elements is carefully monitored and predicted to determine partitioned ranges to become clusters. Considering the change of the data stream, a threshold is adaptively controlled by a prediction mechanism. By predicting the change of supports, the on-going change of a data stream can be reflected in real-time. The proposed method is comparatively analyzed by a series of experiments to identify its various characteristics.
关键词：Data Streams; Clustering; Data mining; Adaptive memory utilization