Abstract
This chapter characterises the scope of this book. It explains the reasons why one should be interested in cluster analysis, lists major application areas, basic theoretical and practical problems, and highlights open research issues and challenges faced by people applying clustering methods.
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Notes
- 1.
See, e.g., J. W. Tukey, Exploratory Data Analysis. Addison-Wesley, 1977.
- 2.
This area is also referred to as Q-analysis, typology, grouping, partitioning, clumping, and taxonomy, [273], depending upon the domain of application.
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Wierzchoń, S.T., Kłopotek, M.A. (2018). Introduction. In: Modern Algorithms of Cluster Analysis. Studies in Big Data, vol 34. Springer, Cham. https://doi.org/10.1007/978-3-319-69308-8_1
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DOI: https://doi.org/10.1007/978-3-319-69308-8_1
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