Adaptive Trace of Multi-dimensional Clusters by Monitoring Data Streams

Provided by: Science & Engineering Research Support soCiety (SERSC)
Topic: Data Management
Format: PDF
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.

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