A survey of clustering data mining techniques

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Abstract

Clustering is the division of data into groups of similar objects. In clustering, some details are disregarded in exchange for data simplification. Clustering can be viewed as a data modeling technique that provides for concise summaries of the data. Clustering is therefore related to many disciplines and plays an important role in a broad range of applications. The applications of clustering usually deal with large datasets and data with many attributes. Exploration of such data is a subject of data mining. This survey concentrates on clustering algorithms from a data mining perspective. © 2006 Springer-Verlag Berlin Heidelberg.

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APA

Berkhin, P. (2006). A survey of clustering data mining techniques. In Grouping Multidimensional Data: Recent Advances in Clustering (pp. 25–71). Springer Berlin Heidelberg. https://doi.org/10.1007/3-540-28349-8_2

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