Scalable Clustering for Large High-Dimensional Data Based on Data Summarization

Clustering large data sets with high dimensionality is a challenging data-mining task. This paper presents a framework to perform such a task efficiently. It is based on the notion of data space reduction, which finds high density areas, or dense cells, in the given feature space. The dense cells st...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Ying Lai, Orlandic, R., Wai Gen Yee, Kulkarni, S.
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Algorithm design and analysis Clustering algorithms Clustering methods Computational intelligence Computer science Data mining Iterative algorithms Partitioning algorithms Sampling methods Space technology
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