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A Survey of Clustering Data Mining Techniques

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Grouping Multidimensional Data

Summary

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.

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© 2006 Springer-Verlag Berlin Heidelberg

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Berkhin, P. (2006). A Survey of Clustering Data Mining Techniques. In: Kogan, J., Nicholas, C., Teboulle, M. (eds) Grouping Multidimensional Data. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-28349-8_2

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  • DOI: https://doi.org/10.1007/3-540-28349-8_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-28348-5

  • Online ISBN: 978-3-540-28349-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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