Definition
A hierarchical clustering method generates a sequence of partitions of data objects. It proceeds successively by either merging smaller clusters into larger ones, or by splitting larger clusters. The result of the algorithm is a tree of clusters, called dendrogram (see Fig. 1), which shows how the clusters are related. By cutting the dendrogram at a desired level, a clustering of the data items into disjointed groups is obtained.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Recommended Reading
Guha S, Rastogi R, Shim K. CURE: An efficient clustering algorithm for large databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 1998. p. 73–84.
Guha S, Rastogi, R, Shim, K. ROCK: a robust clustering algorithm for categorical attributes. In: Proceedings of the 15th International Conference on Data Engineering; 1999. p. 512–21.
Han J, Kamber M. Data mining: concepts and techniques. Morgan Kaufmann; 2001.
Karypis G., Han E.-H., Kumar V. CHAMELEON: a hierarchical clustering algorithm using dynamic modeling. IEEE Comput. 1999;32(8):68–75.
Nanopoulos A, Theodoridis Y, Manolopoulos Y. C2P: clustering based on closest pairs. In: Proceedings of thw 27th International Conference on Very Large Data Bases; 2001. p. 331–40.
Zhang T, Ramakrishnman R, Livny M. BIRCH: an efficient method for very large databases. In: Proceedings of the ACM SIGMOD International Conference on Management of Data; 1996. p. 103–14.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC, part of Springer Nature
About this entry
Cite this entry
Halkidi, M. (2018). Hierarchical Clustering. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_604
Download citation
DOI: https://doi.org/10.1007/978-1-4614-8265-9_604
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-8266-6
Online ISBN: 978-1-4614-8265-9
eBook Packages: Computer ScienceReference Module Computer Science and Engineering